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Browse files- README.md +175 -3
- config.json +29 -0
- generation_config.json +6 -0
- model-00001-of-00008.safetensors +3 -0
- model-00002-of-00008.safetensors +3 -0
- model-00003-of-00008.safetensors +3 -0
- model-00004-of-00008.safetensors +3 -0
- model-00005-of-00008.safetensors +3 -0
- model-00006-of-00008.safetensors +3 -0
- model-00007-of-00008.safetensors +3 -0
- model-00008-of-00008.safetensors +3 -0
- model.safetensors.index.json +766 -0
- special_tokens_map.json +17 -0
- tokenizer.json +0 -0
- tokenizer_config.json +2063 -0
README.md
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---
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license:
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---
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license: apache-2.0
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tags:
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- merge
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- mergekit
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- lazymergetkit
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- sh2orc
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- bccard
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- llama3
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base_model:
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- sh2orc/Llama-3-Kor-BCCard-20B
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---
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**Llama-3-Kor-BCCard-20B** is a Korean financial knowledge model based on Meta-Llama3 8B to 20B parameters through upscaling techniques.
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Although highly reliable data has been refined and fine-tuned using the RLHF method,
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I'm not responsible for any confusion caused by the answers generated by the LLM model.
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- Foundation Model [sh2orc/Llama-3-Kor-BCCard-8B](https://huggingface.co/sh2orc/Llama-3-Kor-BCCard-8B)
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- Dataset
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- [sh2orc/bccard-finance-qna](https://huggingface.co/datasets/sh2orc/bccard-finance-qna)
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# How to Use
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```python
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from vllm import LLM, SamplingParams
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from transformers import AutoTokenizer, pipeline
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BASE_MODEL = "sh2orc/Llama-3-Kor-BCCard-20B"
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llm = LLM(model=BASE_MODEL)
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llm = LLM(model=BASE_MODEL, gpu_memory_utilization=0.95, max_model_len=4096)
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tokenizer.pad_token = tokenizer.eos_token
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tokenizer.padding_side = 'right'
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def gen(instruction):
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messages = [
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{
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"role": "system",
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"content": "당신은 훌륭한 AI 비서입니다. You are a great AI assistant."
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},
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{
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"role": "user",
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"content": instruction
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},
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]
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prompt_message = tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True,
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)
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eos_token_id = [tokenizer.eos_token_id, tokenizer.convert_tokens_to_ids("<|eot_id|>")]
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outputs = llm.generate(prompt_message, SamplingParams(stop_token_ids=eos_token_id, temperature=0.3, top_p=0.9,max_tokens=4096))
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for output in outputs:
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propt = output.prompt
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generated_text = output.outputs[0].text
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print(generated_text)
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gen('비씨카드에 대해서 알려주세요')
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비씨카드는 대한민국에서 오래된 신용카드 회사 중 하나로, 1982년에 설립되었습니다. 2019년에는 본사를 서울 중구 을지로4가 을지트윈타워로 이전하였으며, 대한민국의 여러 시중은행들이 출자하여 설립된 회사입니다. 주로 신용카드와 체크카드를 발급하며, 다양한 상품들은 주로 은행들과 파트너십을 맺어 발행합니다.
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```
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-------
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# Q&A Llama-3-BCCard-12B
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**gen('비씨카드에 대해 알려주세요.')**
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비씨카드는 1982년 4월 10일에 설립된 대한민국의 주요 신용카드 회사입니다. 한국에서 가장 오래된 신용카드 회사 중 하나로, 여러 금융 서비스를 통해 고객에게 편리함과 다양한 혜택을 제공하고 있습니다. 주요 은행들이 공동 출자하여 설립된 이 회사는 신용카드 보급, 금융 서비스 확장, 그리고 금융 기술 혁신을 목표로 하고 있습니다.
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비씨카드는 주로 신용카드와 체크카드 발급에 초점을 맞추고 있으며, 다양한 제휴사와 협력하여 다양한 혜택과 서비스를 제공합니다. 최근는 모바일 결제법과 디지털 지갑 서비스를 발전시키며, 금융 서비스의 편의성을 높이고 있습니다. 또한, 비씨카드는 환경 보호과 같은 사회적 책임도 다하고 있습니다.
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현재 비씨카드의 주요 자회사로는 케이뱅크, H&C네트워크, VP주식회사 등이 있습니다. 비씨카드는 지속적인 혁신과 고객 중심의 서비스를 통해 금융 시장에서의 경쟁력을 강화하고 있습니다.
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**gen('비씨카드 노동조합에 대해서 알려주세요.')**
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비씨카드 노동조합은 비씨카드의 근무 조건, 급여, 퇴직연금, 사회보험 가입 등 근로자들의 권익을 보호하고 강화하는 목적을 위한 계약입니다. 주요 혜택으로는 정기임금 지급, 근무 시간 규정, 퇴직연금 적립, 다양한 사회보험 가입 혜택이 포함됩니다. 이러한 조합은 근로자들의 복지 증진과 노동-경영 상호 이해를 증진시키기 위해 지속적으로 일하고 있습니다.
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**gen('비씨카드 CEO에 대해서 알려주세요.')**
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비씨카드의 현재 CEO는 최원석 사장입니다. 그는 비씨카드의 경영을 이끌며 회사의 전략적 방향 설정, 운영 관리, 그리고 고객 만족도 향상을 위한 다양한 혁신을 추진 중입니다.
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**gen('GOAT카드에 대해서 알려주세요.')**
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GOAT 카드는 해외겸용(MasterCard/VISA) 및 국내 전용 BC카드 모두 가능하며, 연간 개인 사용액에 따라 높은 적립 혜택을 제공합니다. 국제 브랜드 수수료가 1% 있으며, 국내 가맹점 적립률은 국내 사용액 1.5%, 해외 가맹점 적립률은 해외 사용액 3%입니다.
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**gen('케이뱅크에 대해 알려주세요.')**
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케이뱅크는 2017년 4월 3일에 영업을 시작한 대한민국 최초의 인터넷 전문은행. KT가 주요 주주로 있으며, 물리적인 지점 없이 모든 금융 서비스를 온라인과 모바일 앱을 통해 제공합니다. 주요 기능으로는 비대면 계좌 개설, 카드 발급, 대출 서비스, 투자 상품 제공 등이 있습니다. 케이뱅크는 고객 경험을 중심으로 서비스를 개선하고, 다양한 이벤트와 혜택을 제공하여 고객 만족도를 높이고 있습니다.
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**gen('카드 결제했던 가게에서 환불하려니 갔는데 사라졌어. 보상 받을 수 있어?')**
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해당 가맹점에서 15일 내 환불 처리를 요청하지 않으면, 가맹점에서 환불을 처리하지 않거나 자동이체된 경우이므로 카드사에서 환불 처리를 요청해야 합니다. 카드사에 연락하여 취소 내역을 제출하여 환불 절차를 진행하면 됩니다.
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**gen('케이뱅크에서 대출을 받고 싶은데, 카드론 300만원을 받았어, 대출에 미치는 영향에 대해서 알려줘')**
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카드론 300만원을 받았다면, 이는 대출 잔액에 포함되며, 상환 기간에 따라 이자 부담이 증가합니다. 총 대출 금액과 이자 금액을 합산하여 월 상환액을 계산할 수 있으며, 카드론 부분에 따라 상환 기간과 이자율이 달라질 수 있습니다.
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**gen('삼성페이로 보험료 납부 가능해요?')**
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네, 삼성페이를 통해 보험료를 납부할 수 있습니다. 보험사 웹사이트나 애플리케이션에서 삼성페이를 결제 수단으로 선택하여 보험료를 납부할 수 있으며, 이는 빠른하고 편리한 납부 방법입니다.
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**gen('비씨카드와 케이뱅크의 관계는?')**
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비씨카드는 케이뱅크의 최대주주로서 2023년 3월 기준 약 8,616억원의 주식을 보유하고 있습니다. 이는 비씨카드 자기자본의 60%에 해당하며, 비씨카드는 케이뱅크의 경영권을 확보하고 있습니다.
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**gen('케이뱅크는 모바일로만 이용 가능한가요?')**
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케이뱅크는 원래 모바일 전용이었고 여전히 대부분 모바일 이용자가 이용하고 있습니다. 그러나 최근에는 인터넷 뱅킹 서비스도 제공하기 시작했으며, 언제 어디서나 편리하게 은행 거래를 할 수 있는 종합 금융 플랫폼으로 발전하고 있습니다.
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**gen('우리카드가 독자망 구축한다는데 이게 좋은거예요? 아니면 나쁜거예요?')**
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독자망 구축은 단기적으로 비용이 많이 들고, 시스템 안정화 과정에서 새로운 리스크를 겪을 수 있어 어려운 시기입니다. 기존BC카드의 자체 전산망을 구축하여 매출 데이터의 투명성을 높이고, 카드 수수료 절감을 통해 가맹점의 수수료가 인하되지만, 이러한 혜택을 받기까지는 시간이 걸립니다.
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**gen('국내 빅테크사 금융사업에서 사고가 있었던 적이 있나요?')**
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네, 국내 빅테크사 금융사업에서도 여러 사고 사례가 있습니다. 예를 들어, 2023년 네이버페이는 서버 과부하로 인해 대규모 장애가 발생했으며, 이로 인해 많은 사용자들이 결제에 어려움을 겪었습니다. 빅테크사의 과도한 혁신과 단축된 개발 주기, 그리고 보안 취약점 등이 사고를 초래하는 경우가 많습니다.
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**gen('퇴직연금을 DB형이 좋은지 DC형이 좋은지 알려줘')**
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| 123 |
+
DB형 퇴직금은 퇴직소득을 합산하여 퇴직금을 계산하므로, 총 급여액의 10%를 20년 동안 투자하여 누적된 금액을 지급합니다. 반면, DC형 퇴직금은 연간 소득을 합산하여 투자금액을 계산하고, 이자를 지급합니다. 소득액이 많고 노후 전까지만 투자하려면 DB형이 유리하지만, 낮은 소득 시기에 DC형을 선택하는 것이 좋습니다.
|
| 124 |
+
|
| 125 |
+
**gen('iM뱅크에 대해서 설명해줘')**
|
| 126 |
+
iM뱅크는 DGB대구은행의 디지털 뱅킹 서비스로, 스마트폰을 통해 다양한 금융 서비스를 제공하는 은행입니다. 주요 기능은 다음과 같습니다:
|
| 127 |
+
|
| 128 |
+
1. **계좌 조회 및 송금**: iM뱅크를 통해 계좌 현황을 확인하고, 송금할 수 있습니다. 이는 빠르고 간편하게 이용할 수 있어 많은 사용자들이 선호합니다.
|
| 129 |
+
|
| 130 |
+
2. **카드 관리**: 카드 사용 내역 조회, 결제 예정 금액 확인, 분실 신고 등 다양한 카드 관리 서비스가 제공됩니다.
|
| 131 |
+
|
| 132 |
+
3. **대출 신청 및 관리**: 주택담보대출, 전세자금대출, 학자금대출 등 다양한 대출 상품의 신청, 승인 상태 확인, 상환 계획 수립 등의 서비스를 제공합니다.
|
| 133 |
+
|
| 134 |
+
4. **고객 지원 센터**: 실시간 채팅 상담, 유튜브 교육 채널, 다양한 가이드라인 등을 통해 고객의 금융 문의에 대응합니다.
|
| 135 |
+
|
| 136 |
+
5. **포인트 적립 및 혜택**: 카드 사용 시 포인트를 적립하고, 제휴 가맹점에서 현금처럼 사용할 수 있습니다.
|
| 137 |
+
|
| 138 |
+
iM뱅크는 사용자 경험을 최우선으로 하여 편리한 금융 서비스를 제공하며, 다양한 혜택을 통해 고객 충성도를 높이고 있습니다.
|
| 139 |
+
|
| 140 |
+
|
| 141 |
+
**gen('K패스카드가 인기 있는 이유를 요약. 그리고 혜택에 대해 상세히 알려줘')**
|
| 142 |
+
K-패스 카드는 대중교통, OTT 서비스, 편의점, 이동통신 요금 등 다양한 분야에서 할인 혜택을 제공하여 많은 인기를 끌고 있습니다. 특히 청년 고객의 경우 최대 15%의 통신요금 할인과 대중교통 할인 혜택이 인기가 높아 이용이 많은 편입니다.
|
| 143 |
+
|
| 144 |
+
**gen('IBK기업은행 신용카드 추천해줘')**
|
| 145 |
+
IBK기업은행에서 제공하는 신용카드에는 다양한 혜택이 있는 카드들이 있습니다. 여행을 자주 하시는 분에게는 IBK기업은행 플래티늄카드나 IBK기업은행 ROB카드가 적합합니다. 플래티늄카드는 전 세계 600여 개 공항 라운지 이용, 국제선 동반자 무료항공권 등에 대한 혜택을 제공하며, ROB카드는 대한항공 마일리지 적립에 특화되어 있습니다. 가족, 친구들과 함께 여행을 자주 다니시는 분들께 적합합니다.
|
| 146 |
+
|
| 147 |
+
**gen('나는 해외여행을 가려고 해. 주의사항과 여행에 좋은 신용카드 추천해줘')**
|
| 148 |
+
해외여행을 계획하시면 BC바로 리워드 플러스 카드를 추천드립니다. 이 카드는 해외 결제 시 높은 적립률을 제공하며, 해외 여행에 적합한 다양한 혜택을 누리실 수 있습니다.
|
| 149 |
+
|
| 150 |
+
**gen('퇴직연금 투자 시 직접 투자를 운용하는게 좋을까? ETF를 투자하는게 좋을까?')**
|
| 151 |
+
퇴직연금 투자 시 직접 투자를 운용하는 것도 좋은 선택입니다. 직접 투자하면 자신의 투자 성향에 맞게 포트폴리오를 구성할 수 있으며, 높은 수익을 기대할 수 있습니다. 그러나 직접 투자 시에는 주식시장 변동성에 따른 리스크도 부담해야 합니다. 반면, ETF는 분산 투자 효과를 얻을 수 있어 리스크를 줄일 수 있습니다. 본인의 투자 경험이 많고 리스크를 감수하는 방향으로 선택하는 것이 좋습니다.
|
| 152 |
+
|
| 153 |
+
**gen('신용 연체에 따른 부작용에 대해서 알려줘')**
|
| 154 |
+
신용 연체는 신용등급 하락으로 이어질 수 있으며, 이는 다른 금융 거래에도 부정적인 영향을 미칠 수 있습니다. 채권 금융에 특히 신용등급이 중요한 요소로 작용합니다.
|
| 155 |
+
|
| 156 |
+
|
| 157 |
+
|
| 158 |
+
## Correspondence to
|
| 159 |
+
- Taeyoung Lee ([email protected])
|
| 160 |
+
|
| 161 |
+
## License
|
| 162 |
+
The use of this model is governed by the [META LLAMA 3 COMMUNITY LICENSE AGREEMENT](https://llama.meta.com/llama3/license/)
|
| 163 |
+
|
| 164 |
+
## Citation
|
| 165 |
+
If you use this model in your research, please cite it as follows:
|
| 166 |
+
|
| 167 |
+
```bibtex
|
| 168 |
+
@misc{alpha-instruct,
|
| 169 |
+
author = {Taeyoung Lee},
|
| 170 |
+
year = {2024},
|
| 171 |
+
publisher = {Hugging Face},
|
| 172 |
+
journal = {Hugging Face repository},
|
| 173 |
+
url = {https://huggingface.co/sh2orc/Llama-3-Kor-BCCard-12B},
|
| 174 |
+
}
|
| 175 |
+
|
config.json
ADDED
|
@@ -0,0 +1,29 @@
|
|
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|
| 1 |
+
{
|
| 2 |
+
"_name_or_path": "bccard-20b",
|
| 3 |
+
"architectures": [
|
| 4 |
+
"LlamaForCausalLM"
|
| 5 |
+
],
|
| 6 |
+
"attention_bias": false,
|
| 7 |
+
"attention_dropout": 0.0,
|
| 8 |
+
"bos_token_id": 144782,
|
| 9 |
+
"eos_token_id": 144783,
|
| 10 |
+
"hidden_act": "silu",
|
| 11 |
+
"hidden_size": 4096,
|
| 12 |
+
"initializer_range": 0.02,
|
| 13 |
+
"intermediate_size": 14336,
|
| 14 |
+
"max_position_embeddings": 8192,
|
| 15 |
+
"mlp_bias": false,
|
| 16 |
+
"model_type": "llama",
|
| 17 |
+
"num_attention_heads": 32,
|
| 18 |
+
"num_hidden_layers": 84,
|
| 19 |
+
"num_key_value_heads": 8,
|
| 20 |
+
"pretraining_tp": 1,
|
| 21 |
+
"rms_norm_eps": 1e-05,
|
| 22 |
+
"rope_scaling": null,
|
| 23 |
+
"rope_theta": 500000.0,
|
| 24 |
+
"tie_word_embeddings": false,
|
| 25 |
+
"torch_dtype": "bfloat16",
|
| 26 |
+
"transformers_version": "4.40.0",
|
| 27 |
+
"use_cache": true,
|
| 28 |
+
"vocab_size": 145088
|
| 29 |
+
}
|
generation_config.json
ADDED
|
@@ -0,0 +1,6 @@
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|
| 1 |
+
{
|
| 2 |
+
"_from_model_config": true,
|
| 3 |
+
"bos_token_id": 144782,
|
| 4 |
+
"eos_token_id": 144783,
|
| 5 |
+
"transformers_version": "4.40.0"
|
| 6 |
+
}
|
model-00001-of-00008.safetensors
ADDED
|
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| 1 |
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|
| 3 |
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ADDED
|
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| 1 |
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model-00003-of-00008.safetensors
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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model.safetensors.index.json
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special_tokens_map.json
ADDED
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|
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tokenizer.json
ADDED
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tokenizer_config.json
ADDED
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|
| 1 |
+
{
|
| 2 |
+
"added_tokens_decoder": {
|
| 3 |
+
"144782": {
|
| 4 |
+
"content": "<|begin_of_text|>",
|
| 5 |
+
"lstrip": false,
|
| 6 |
+
"normalized": false,
|
| 7 |
+
"rstrip": false,
|
| 8 |
+
"single_word": false,
|
| 9 |
+
"special": true
|
| 10 |
+
},
|
| 11 |
+
"144783": {
|
| 12 |
+
"content": "<|end_of_text|>",
|
| 13 |
+
"lstrip": false,
|
| 14 |
+
"normalized": false,
|
| 15 |
+
"rstrip": false,
|
| 16 |
+
"single_word": false,
|
| 17 |
+
"special": true
|
| 18 |
+
},
|
| 19 |
+
"144784": {
|
| 20 |
+
"content": "<|reserved_special_token_0|>",
|
| 21 |
+
"lstrip": false,
|
| 22 |
+
"normalized": false,
|
| 23 |
+
"rstrip": false,
|
| 24 |
+
"single_word": false,
|
| 25 |
+
"special": true
|
| 26 |
+
},
|
| 27 |
+
"144785": {
|
| 28 |
+
"content": "<|reserved_special_token_1|>",
|
| 29 |
+
"lstrip": false,
|
| 30 |
+
"normalized": false,
|
| 31 |
+
"rstrip": false,
|
| 32 |
+
"single_word": false,
|
| 33 |
+
"special": true
|
| 34 |
+
},
|
| 35 |
+
"144786": {
|
| 36 |
+
"content": "<|reserved_special_token_2|>",
|
| 37 |
+
"lstrip": false,
|
| 38 |
+
"normalized": false,
|
| 39 |
+
"rstrip": false,
|
| 40 |
+
"single_word": false,
|
| 41 |
+
"special": true
|
| 42 |
+
},
|
| 43 |
+
"144787": {
|
| 44 |
+
"content": "<|reserved_special_token_3|>",
|
| 45 |
+
"lstrip": false,
|
| 46 |
+
"normalized": false,
|
| 47 |
+
"rstrip": false,
|
| 48 |
+
"single_word": false,
|
| 49 |
+
"special": true
|
| 50 |
+
},
|
| 51 |
+
"144788": {
|
| 52 |
+
"content": "<|start_header_id|>",
|
| 53 |
+
"lstrip": false,
|
| 54 |
+
"normalized": false,
|
| 55 |
+
"rstrip": false,
|
| 56 |
+
"single_word": false,
|
| 57 |
+
"special": true
|
| 58 |
+
},
|
| 59 |
+
"144789": {
|
| 60 |
+
"content": "<|end_header_id|>",
|
| 61 |
+
"lstrip": false,
|
| 62 |
+
"normalized": false,
|
| 63 |
+
"rstrip": false,
|
| 64 |
+
"single_word": false,
|
| 65 |
+
"special": true
|
| 66 |
+
},
|
| 67 |
+
"144790": {
|
| 68 |
+
"content": "<|reserved_special_token_4|>",
|
| 69 |
+
"lstrip": false,
|
| 70 |
+
"normalized": false,
|
| 71 |
+
"rstrip": false,
|
| 72 |
+
"single_word": false,
|
| 73 |
+
"special": true
|
| 74 |
+
},
|
| 75 |
+
"144791": {
|
| 76 |
+
"content": "<|eot_id|>",
|
| 77 |
+
"lstrip": false,
|
| 78 |
+
"normalized": false,
|
| 79 |
+
"rstrip": false,
|
| 80 |
+
"single_word": false,
|
| 81 |
+
"special": true
|
| 82 |
+
},
|
| 83 |
+
"144792": {
|
| 84 |
+
"content": "<|reserved_special_token_5|>",
|
| 85 |
+
"lstrip": false,
|
| 86 |
+
"normalized": false,
|
| 87 |
+
"rstrip": false,
|
| 88 |
+
"single_word": false,
|
| 89 |
+
"special": true
|
| 90 |
+
},
|
| 91 |
+
"144793": {
|
| 92 |
+
"content": "<|reserved_special_token_6|>",
|
| 93 |
+
"lstrip": false,
|
| 94 |
+
"normalized": false,
|
| 95 |
+
"rstrip": false,
|
| 96 |
+
"single_word": false,
|
| 97 |
+
"special": true
|
| 98 |
+
},
|
| 99 |
+
"144794": {
|
| 100 |
+
"content": "<|reserved_special_token_7|>",
|
| 101 |
+
"lstrip": false,
|
| 102 |
+
"normalized": false,
|
| 103 |
+
"rstrip": false,
|
| 104 |
+
"single_word": false,
|
| 105 |
+
"special": true
|
| 106 |
+
},
|
| 107 |
+
"144795": {
|
| 108 |
+
"content": "<|reserved_special_token_8|>",
|
| 109 |
+
"lstrip": false,
|
| 110 |
+
"normalized": false,
|
| 111 |
+
"rstrip": false,
|
| 112 |
+
"single_word": false,
|
| 113 |
+
"special": true
|
| 114 |
+
},
|
| 115 |
+
"144796": {
|
| 116 |
+
"content": "<|reserved_special_token_9|>",
|
| 117 |
+
"lstrip": false,
|
| 118 |
+
"normalized": false,
|
| 119 |
+
"rstrip": false,
|
| 120 |
+
"single_word": false,
|
| 121 |
+
"special": true
|
| 122 |
+
},
|
| 123 |
+
"144797": {
|
| 124 |
+
"content": "<|reserved_special_token_10|>",
|
| 125 |
+
"lstrip": false,
|
| 126 |
+
"normalized": false,
|
| 127 |
+
"rstrip": false,
|
| 128 |
+
"single_word": false,
|
| 129 |
+
"special": true
|
| 130 |
+
},
|
| 131 |
+
"144798": {
|
| 132 |
+
"content": "<|reserved_special_token_11|>",
|
| 133 |
+
"lstrip": false,
|
| 134 |
+
"normalized": false,
|
| 135 |
+
"rstrip": false,
|
| 136 |
+
"single_word": false,
|
| 137 |
+
"special": true
|
| 138 |
+
},
|
| 139 |
+
"144799": {
|
| 140 |
+
"content": "<|reserved_special_token_12|>",
|
| 141 |
+
"lstrip": false,
|
| 142 |
+
"normalized": false,
|
| 143 |
+
"rstrip": false,
|
| 144 |
+
"single_word": false,
|
| 145 |
+
"special": true
|
| 146 |
+
},
|
| 147 |
+
"144800": {
|
| 148 |
+
"content": "<|reserved_special_token_13|>",
|
| 149 |
+
"lstrip": false,
|
| 150 |
+
"normalized": false,
|
| 151 |
+
"rstrip": false,
|
| 152 |
+
"single_word": false,
|
| 153 |
+
"special": true
|
| 154 |
+
},
|
| 155 |
+
"144801": {
|
| 156 |
+
"content": "<|reserved_special_token_14|>",
|
| 157 |
+
"lstrip": false,
|
| 158 |
+
"normalized": false,
|
| 159 |
+
"rstrip": false,
|
| 160 |
+
"single_word": false,
|
| 161 |
+
"special": true
|
| 162 |
+
},
|
| 163 |
+
"144802": {
|
| 164 |
+
"content": "<|reserved_special_token_15|>",
|
| 165 |
+
"lstrip": false,
|
| 166 |
+
"normalized": false,
|
| 167 |
+
"rstrip": false,
|
| 168 |
+
"single_word": false,
|
| 169 |
+
"special": true
|
| 170 |
+
},
|
| 171 |
+
"144803": {
|
| 172 |
+
"content": "<|reserved_special_token_16|>",
|
| 173 |
+
"lstrip": false,
|
| 174 |
+
"normalized": false,
|
| 175 |
+
"rstrip": false,
|
| 176 |
+
"single_word": false,
|
| 177 |
+
"special": true
|
| 178 |
+
},
|
| 179 |
+
"144804": {
|
| 180 |
+
"content": "<|reserved_special_token_17|>",
|
| 181 |
+
"lstrip": false,
|
| 182 |
+
"normalized": false,
|
| 183 |
+
"rstrip": false,
|
| 184 |
+
"single_word": false,
|
| 185 |
+
"special": true
|
| 186 |
+
},
|
| 187 |
+
"144805": {
|
| 188 |
+
"content": "<|reserved_special_token_18|>",
|
| 189 |
+
"lstrip": false,
|
| 190 |
+
"normalized": false,
|
| 191 |
+
"rstrip": false,
|
| 192 |
+
"single_word": false,
|
| 193 |
+
"special": true
|
| 194 |
+
},
|
| 195 |
+
"144806": {
|
| 196 |
+
"content": "<|reserved_special_token_19|>",
|
| 197 |
+
"lstrip": false,
|
| 198 |
+
"normalized": false,
|
| 199 |
+
"rstrip": false,
|
| 200 |
+
"single_word": false,
|
| 201 |
+
"special": true
|
| 202 |
+
},
|
| 203 |
+
"144807": {
|
| 204 |
+
"content": "<|reserved_special_token_20|>",
|
| 205 |
+
"lstrip": false,
|
| 206 |
+
"normalized": false,
|
| 207 |
+
"rstrip": false,
|
| 208 |
+
"single_word": false,
|
| 209 |
+
"special": true
|
| 210 |
+
},
|
| 211 |
+
"144808": {
|
| 212 |
+
"content": "<|reserved_special_token_21|>",
|
| 213 |
+
"lstrip": false,
|
| 214 |
+
"normalized": false,
|
| 215 |
+
"rstrip": false,
|
| 216 |
+
"single_word": false,
|
| 217 |
+
"special": true
|
| 218 |
+
},
|
| 219 |
+
"144809": {
|
| 220 |
+
"content": "<|reserved_special_token_22|>",
|
| 221 |
+
"lstrip": false,
|
| 222 |
+
"normalized": false,
|
| 223 |
+
"rstrip": false,
|
| 224 |
+
"single_word": false,
|
| 225 |
+
"special": true
|
| 226 |
+
},
|
| 227 |
+
"144810": {
|
| 228 |
+
"content": "<|reserved_special_token_23|>",
|
| 229 |
+
"lstrip": false,
|
| 230 |
+
"normalized": false,
|
| 231 |
+
"rstrip": false,
|
| 232 |
+
"single_word": false,
|
| 233 |
+
"special": true
|
| 234 |
+
},
|
| 235 |
+
"144811": {
|
| 236 |
+
"content": "<|reserved_special_token_24|>",
|
| 237 |
+
"lstrip": false,
|
| 238 |
+
"normalized": false,
|
| 239 |
+
"rstrip": false,
|
| 240 |
+
"single_word": false,
|
| 241 |
+
"special": true
|
| 242 |
+
},
|
| 243 |
+
"144812": {
|
| 244 |
+
"content": "<|reserved_special_token_25|>",
|
| 245 |
+
"lstrip": false,
|
| 246 |
+
"normalized": false,
|
| 247 |
+
"rstrip": false,
|
| 248 |
+
"single_word": false,
|
| 249 |
+
"special": true
|
| 250 |
+
},
|
| 251 |
+
"144813": {
|
| 252 |
+
"content": "<|reserved_special_token_26|>",
|
| 253 |
+
"lstrip": false,
|
| 254 |
+
"normalized": false,
|
| 255 |
+
"rstrip": false,
|
| 256 |
+
"single_word": false,
|
| 257 |
+
"special": true
|
| 258 |
+
},
|
| 259 |
+
"144814": {
|
| 260 |
+
"content": "<|reserved_special_token_27|>",
|
| 261 |
+
"lstrip": false,
|
| 262 |
+
"normalized": false,
|
| 263 |
+
"rstrip": false,
|
| 264 |
+
"single_word": false,
|
| 265 |
+
"special": true
|
| 266 |
+
},
|
| 267 |
+
"144815": {
|
| 268 |
+
"content": "<|reserved_special_token_28|>",
|
| 269 |
+
"lstrip": false,
|
| 270 |
+
"normalized": false,
|
| 271 |
+
"rstrip": false,
|
| 272 |
+
"single_word": false,
|
| 273 |
+
"special": true
|
| 274 |
+
},
|
| 275 |
+
"144816": {
|
| 276 |
+
"content": "<|reserved_special_token_29|>",
|
| 277 |
+
"lstrip": false,
|
| 278 |
+
"normalized": false,
|
| 279 |
+
"rstrip": false,
|
| 280 |
+
"single_word": false,
|
| 281 |
+
"special": true
|
| 282 |
+
},
|
| 283 |
+
"144817": {
|
| 284 |
+
"content": "<|reserved_special_token_30|>",
|
| 285 |
+
"lstrip": false,
|
| 286 |
+
"normalized": false,
|
| 287 |
+
"rstrip": false,
|
| 288 |
+
"single_word": false,
|
| 289 |
+
"special": true
|
| 290 |
+
},
|
| 291 |
+
"144818": {
|
| 292 |
+
"content": "<|reserved_special_token_31|>",
|
| 293 |
+
"lstrip": false,
|
| 294 |
+
"normalized": false,
|
| 295 |
+
"rstrip": false,
|
| 296 |
+
"single_word": false,
|
| 297 |
+
"special": true
|
| 298 |
+
},
|
| 299 |
+
"144819": {
|
| 300 |
+
"content": "<|reserved_special_token_32|>",
|
| 301 |
+
"lstrip": false,
|
| 302 |
+
"normalized": false,
|
| 303 |
+
"rstrip": false,
|
| 304 |
+
"single_word": false,
|
| 305 |
+
"special": true
|
| 306 |
+
},
|
| 307 |
+
"144820": {
|
| 308 |
+
"content": "<|reserved_special_token_33|>",
|
| 309 |
+
"lstrip": false,
|
| 310 |
+
"normalized": false,
|
| 311 |
+
"rstrip": false,
|
| 312 |
+
"single_word": false,
|
| 313 |
+
"special": true
|
| 314 |
+
},
|
| 315 |
+
"144821": {
|
| 316 |
+
"content": "<|reserved_special_token_34|>",
|
| 317 |
+
"lstrip": false,
|
| 318 |
+
"normalized": false,
|
| 319 |
+
"rstrip": false,
|
| 320 |
+
"single_word": false,
|
| 321 |
+
"special": true
|
| 322 |
+
},
|
| 323 |
+
"144822": {
|
| 324 |
+
"content": "<|reserved_special_token_35|>",
|
| 325 |
+
"lstrip": false,
|
| 326 |
+
"normalized": false,
|
| 327 |
+
"rstrip": false,
|
| 328 |
+
"single_word": false,
|
| 329 |
+
"special": true
|
| 330 |
+
},
|
| 331 |
+
"144823": {
|
| 332 |
+
"content": "<|reserved_special_token_36|>",
|
| 333 |
+
"lstrip": false,
|
| 334 |
+
"normalized": false,
|
| 335 |
+
"rstrip": false,
|
| 336 |
+
"single_word": false,
|
| 337 |
+
"special": true
|
| 338 |
+
},
|
| 339 |
+
"144824": {
|
| 340 |
+
"content": "<|reserved_special_token_37|>",
|
| 341 |
+
"lstrip": false,
|
| 342 |
+
"normalized": false,
|
| 343 |
+
"rstrip": false,
|
| 344 |
+
"single_word": false,
|
| 345 |
+
"special": true
|
| 346 |
+
},
|
| 347 |
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| 1576 |
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| 1577 |
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|
| 1578 |
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| 1579 |
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|
| 1580 |
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| 1581 |
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| 1582 |
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| 1584 |
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| 1585 |
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|
| 1586 |
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| 1587 |
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|
| 1588 |
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|
| 1589 |
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| 1590 |
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| 1592 |
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| 1593 |
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| 1594 |
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| 1595 |
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|
| 1596 |
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| 1597 |
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| 1601 |
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| 1602 |
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| 1603 |
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|
| 1604 |
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| 1605 |
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| 1606 |
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| 1609 |
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| 1610 |
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| 1611 |
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|
| 1612 |
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| 1613 |
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| 1618 |
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| 1620 |
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| 1621 |
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| 1626 |
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| 1628 |
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| 1629 |
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| 1652 |
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| 1660 |
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| 1666 |
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| 1676 |
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| 1682 |
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| 1684 |
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| 1685 |
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| 1690 |
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| 1692 |
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| 1693 |
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| 1700 |
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| 1738 |
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| 1748 |
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| 1754 |
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| 1756 |
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| 1772 |
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| 1780 |
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| 1786 |
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| 1788 |
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| 1790 |
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| 1793 |
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|
| 1794 |
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| 1795 |
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| 1796 |
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| 1797 |
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| 1798 |
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| 1800 |
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| 1801 |
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| 1802 |
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| 1803 |
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| 1804 |
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| 1805 |
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| 1806 |
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| 1809 |
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| 1810 |
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| 1811 |
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| 1812 |
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| 1813 |
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| 1814 |
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| 1817 |
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|
| 1818 |
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|
| 1819 |
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|
| 1820 |
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| 1821 |
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| 1822 |
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| 1823 |
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| 1825 |
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| 1826 |
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| 1827 |
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|
| 1828 |
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|
| 1829 |
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|
| 1830 |
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|
| 1831 |
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| 1832 |
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| 1833 |
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|
| 1834 |
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| 1835 |
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|
| 1836 |
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| 1837 |
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| 1838 |
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| 1839 |
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| 1840 |
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|
| 1841 |
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|
| 1842 |
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|
| 1843 |
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|
| 1844 |
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|
| 1845 |
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| 1846 |
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|
| 1847 |
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| 1848 |
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| 1849 |
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|
| 1850 |
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|
| 1851 |
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|
| 1852 |
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|
| 1853 |
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|
| 1854 |
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|
| 1855 |
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| 1856 |
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| 1857 |
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|
| 1858 |
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|
| 1859 |
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|
| 1860 |
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|
| 1861 |
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|
| 1862 |
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|
| 1863 |
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|
| 1864 |
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|
| 1865 |
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|
| 1866 |
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|
| 1867 |
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|
| 1868 |
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|
| 1869 |
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|
| 1870 |
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|
| 1871 |
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| 1872 |
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| 1873 |
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|
| 1874 |
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|
| 1875 |
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|
| 1876 |
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|
| 1877 |
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|
| 1878 |
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|
| 1879 |
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|
| 1880 |
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|
| 1881 |
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|
| 1882 |
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|
| 1883 |
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|
| 1884 |
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|
| 1885 |
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|
| 1886 |
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|
| 1887 |
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|
| 1888 |
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|
| 1889 |
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|
| 1890 |
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|
| 1891 |
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|
| 1892 |
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|
| 1893 |
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|
| 1894 |
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|
| 1895 |
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|
| 1896 |
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|
| 1897 |
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|
| 1898 |
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|
| 1899 |
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|
| 1900 |
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|
| 1901 |
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|
| 1902 |
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|
| 1903 |
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| 1904 |
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| 1905 |
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|
| 1906 |
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|
| 1907 |
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|
| 1908 |
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|
| 1909 |
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|
| 1910 |
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|
| 1911 |
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|
| 1912 |
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|
| 1913 |
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|
| 1914 |
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|
| 1915 |
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|
| 1916 |
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|
| 1917 |
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|
| 1918 |
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|
| 1919 |
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|
| 1920 |
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|
| 1921 |
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|
| 1922 |
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|
| 1923 |
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|
| 1924 |
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"content": "<|reserved_special_token_235|>",
|
| 1925 |
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|
| 1926 |
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|
| 1927 |
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|
| 1928 |
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|
| 1929 |
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|
| 1930 |
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},
|
| 1931 |
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|
| 1932 |
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"content": "<|reserved_special_token_236|>",
|
| 1933 |
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|
| 1934 |
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|
| 1935 |
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|
| 1936 |
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|
| 1937 |
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|
| 1938 |
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},
|
| 1939 |
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"145024": {
|
| 1940 |
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"content": "<|reserved_special_token_237|>",
|
| 1941 |
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|
| 1942 |
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|
| 1943 |
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|
| 1944 |
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|
| 1945 |
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|
| 1946 |
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},
|
| 1947 |
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"145025": {
|
| 1948 |
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"content": "<|reserved_special_token_238|>",
|
| 1949 |
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|
| 1950 |
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|
| 1951 |
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|
| 1952 |
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|
| 1953 |
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|
| 1954 |
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},
|
| 1955 |
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"145026": {
|
| 1956 |
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"content": "<|reserved_special_token_239|>",
|
| 1957 |
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|
| 1958 |
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|
| 1959 |
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|
| 1960 |
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|
| 1961 |
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|
| 1962 |
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},
|
| 1963 |
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"145027": {
|
| 1964 |
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"content": "<|reserved_special_token_240|>",
|
| 1965 |
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|
| 1966 |
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|
| 1967 |
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|
| 1968 |
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|
| 1969 |
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|
| 1970 |
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},
|
| 1971 |
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"145028": {
|
| 1972 |
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"content": "<|reserved_special_token_241|>",
|
| 1973 |
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|
| 1974 |
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|
| 1975 |
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|
| 1976 |
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|
| 1977 |
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|
| 1978 |
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},
|
| 1979 |
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"145029": {
|
| 1980 |
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"content": "<|reserved_special_token_242|>",
|
| 1981 |
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|
| 1982 |
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|
| 1983 |
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|
| 1984 |
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|
| 1985 |
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"special": true
|
| 1986 |
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},
|
| 1987 |
+
"145030": {
|
| 1988 |
+
"content": "<|reserved_special_token_243|>",
|
| 1989 |
+
"lstrip": false,
|
| 1990 |
+
"normalized": false,
|
| 1991 |
+
"rstrip": false,
|
| 1992 |
+
"single_word": false,
|
| 1993 |
+
"special": true
|
| 1994 |
+
},
|
| 1995 |
+
"145031": {
|
| 1996 |
+
"content": "<|reserved_special_token_244|>",
|
| 1997 |
+
"lstrip": false,
|
| 1998 |
+
"normalized": false,
|
| 1999 |
+
"rstrip": false,
|
| 2000 |
+
"single_word": false,
|
| 2001 |
+
"special": true
|
| 2002 |
+
},
|
| 2003 |
+
"145032": {
|
| 2004 |
+
"content": "<|reserved_special_token_245|>",
|
| 2005 |
+
"lstrip": false,
|
| 2006 |
+
"normalized": false,
|
| 2007 |
+
"rstrip": false,
|
| 2008 |
+
"single_word": false,
|
| 2009 |
+
"special": true
|
| 2010 |
+
},
|
| 2011 |
+
"145033": {
|
| 2012 |
+
"content": "<|reserved_special_token_246|>",
|
| 2013 |
+
"lstrip": false,
|
| 2014 |
+
"normalized": false,
|
| 2015 |
+
"rstrip": false,
|
| 2016 |
+
"single_word": false,
|
| 2017 |
+
"special": true
|
| 2018 |
+
},
|
| 2019 |
+
"145034": {
|
| 2020 |
+
"content": "<|reserved_special_token_247|>",
|
| 2021 |
+
"lstrip": false,
|
| 2022 |
+
"normalized": false,
|
| 2023 |
+
"rstrip": false,
|
| 2024 |
+
"single_word": false,
|
| 2025 |
+
"special": true
|
| 2026 |
+
},
|
| 2027 |
+
"145035": {
|
| 2028 |
+
"content": "<|reserved_special_token_248|>",
|
| 2029 |
+
"lstrip": false,
|
| 2030 |
+
"normalized": false,
|
| 2031 |
+
"rstrip": false,
|
| 2032 |
+
"single_word": false,
|
| 2033 |
+
"special": true
|
| 2034 |
+
},
|
| 2035 |
+
"145036": {
|
| 2036 |
+
"content": "<|reserved_special_token_249|>",
|
| 2037 |
+
"lstrip": false,
|
| 2038 |
+
"normalized": false,
|
| 2039 |
+
"rstrip": false,
|
| 2040 |
+
"single_word": false,
|
| 2041 |
+
"special": true
|
| 2042 |
+
},
|
| 2043 |
+
"145037": {
|
| 2044 |
+
"content": "<|reserved_special_token_250|>",
|
| 2045 |
+
"lstrip": false,
|
| 2046 |
+
"normalized": false,
|
| 2047 |
+
"rstrip": false,
|
| 2048 |
+
"single_word": false,
|
| 2049 |
+
"special": true
|
| 2050 |
+
}
|
| 2051 |
+
},
|
| 2052 |
+
"bos_token": "<|begin_of_text|>",
|
| 2053 |
+
"chat_template": "{% set loop_messages = messages %}{% for message in loop_messages %}{% set content = '<|start_header_id|>' + message['role'] + '<|end_header_id|>\n\n'+ message['content'] | trim + '<|eot_id|>' %}{% if loop.index0 == 0 %}{% set content = bos_token + content %}{% endif %}{{ content }}{% endfor %}{% if add_generation_prompt %}{{ '<|start_header_id|>assistant<|end_header_id|>\n\n' }}{% endif %}",
|
| 2054 |
+
"clean_up_tokenization_spaces": true,
|
| 2055 |
+
"eos_token": "<|end_of_text|>",
|
| 2056 |
+
"model_input_names": [
|
| 2057 |
+
"input_ids",
|
| 2058 |
+
"attention_mask"
|
| 2059 |
+
],
|
| 2060 |
+
"model_max_length": 1000000000000000019884624838656,
|
| 2061 |
+
"pad_token": "<|end_of_text|>",
|
| 2062 |
+
"tokenizer_class": "PreTrainedTokenizerFast"
|
| 2063 |
+
}
|