0xtaipoian
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Update README.md
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README.md
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@@ -46,7 +46,7 @@ You can run it on [Colab](https://colab.research.google.com/drive/1FgdwkkPcLzn_x
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from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig, LlamaTokenizer, GenerationConfig, pipeline
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from peft import PeftModel, PeftMixedModel
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import torch
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model_name = "0xtaipoian/open-lilm"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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torch_dtype=torch.bfloat16,
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device_map='auto',
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trust_remote_code=True,
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quantization_config=bnb_config,
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)
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def chat(messages, temperature=0.9, max_new_tokens=200):
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input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt').to('cuda:0')
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output_ids = model.generate(input_ids, max_new_tokens=max_new_tokens, temperature=temperature, do_sample=True)
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"content":
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"""
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密陽44人輪姦案」受害女隔20年現身:時間停在2004
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南韓密陽2004年曾發生一起44人輪姦一位14歲少女案件,44名加害者當時幾乎都未成年,
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法官輕判引起社會聲浪抗議。案件如今過了20年,當年只有14歲的少女與妹妹相隔20年現
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身,近日接受節目《想知道真相》訪問,坦言沒有藥物無法生活,時間就此停在了2004年
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走不出來,「我的夢想是什麼,我不記得了。」只希望家人們從惡夢裡逃脫,過著幸福日
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子。
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"""}]
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result = chat(messages, max_new_tokens=200, temperature=1)
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from transformers import AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig, LlamaTokenizer, GenerationConfig, pipeline
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from peft import PeftModel, PeftMixedModel
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import torch
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model_name = "0xtaipoian/open-lilm"
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tokenizer = AutoTokenizer.from_pretrained(model_name)
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model = AutoModelForCausalLM.from_pretrained(
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model_name,
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revision="main", #qlora-merged (qLoRA finetuned for 3 epochs) or main (full parameter finetune for 1 epoch)
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torch_dtype=torch.bfloat16,
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trust_remote_code=True,
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quantization_config=bnb_config,
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)
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def chat(messages, temperature=0.9, max_new_tokens=200):
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input_ids = tokenizer.apply_chat_template(conversation=messages, tokenize=True, add_generation_prompt=True, return_tensors='pt').to('cuda:0')
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output_ids = model.generate(input_ids, max_new_tokens=max_new_tokens, temperature=temperature, do_sample=True)
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"content":
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"""
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密陽44人輪姦案」受害女隔20年現身:時間停在2004,不記得
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"""}]
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result = chat(messages, max_new_tokens=200, temperature=1)
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