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README.md ADDED
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+ ---
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+ base_model:
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+ - tokyotech-llm/Swallow-70b-instruct-hf
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+ - nitky/Swallow-70b-NVE-RP
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+ tags:
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+ - mergekit
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+ - merge
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+ language:
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+ - en
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+ - ja
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+ library_name: transformers
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+ pipeline_tag: text-generation
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+ license: llama2
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+ model_type: llama
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+ ---
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+ # Swallow-70b-RP
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+
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+ **Important Notice:**
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+
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+ For personal and academic use only.
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+
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+ ## Description
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+
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+ This model is suitable for role-playing and storytelling, but it's not a great model for multi-turn chat.
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+
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+ This was created for personal and academic use only. This merge model uses only fine-tune models of Llama2, but some of the models used include those whose licenses for commercial use are unclear.
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+
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+ If there is a license problem, the rights holder should contact me directly. No license changes will be made due to contact from others.
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+
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+ ## Test environment
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+
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+ This model was tested using [text-generation-webui](https://github.com/oobabooga/text-generation-webui/tree/main). I use preset `simple-1` and `Null preset` for Generation.
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+
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+ ### Recommendation
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+
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+ Use `simple-1` settings:
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+ - temperature: 0.7
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+ - top_p: 0.9
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+ - repetition_penalty: 1.15
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+ - top_k: 20
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+
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+ ### Tested `temperature` Range
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+
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+ - temperature: 0.3 - 1.0
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+
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+ ### Tested `repetition_penalty` Range
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+
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+ - repetition_penalty: 1.0 - 1.15
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+
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+ ## Prompt template
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+
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+ ### Swallow Style (Alpaca format)
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+
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+ ```
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+ 以下に、あるタスクを説明する指示があり、それに付随する入力が更なる文脈を提供しています。リクエストを適切に完了するための回答を記述してください。
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+
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+ ### 指示:
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+ {instruction}
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+
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+ ### 応答:
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+
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+ ```
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+
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+ Although not fully tested, [Doctor-Shotgun/lzlv-limarpv3-l2-70b](Doctor-Shotgun/lzlv-limarpv3-l2-70b) and [alac/Waxwing-Storytelling-70B-LoRA](https://huggingface.co/alac/Waxwing-Storytelling-70B-LoRA) prompt styles are also available.
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+
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+ ## Use the instruct model
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+
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+ ```
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+ import torch
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+ from transformers import AutoTokenizer, AutoModelForCausalLM
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+
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+ model_name = "nitky/Swallow-70b-RP"
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+
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+ tokenizer = AutoTokenizer.from_pretrained(model_name)
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+ model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, low_cpu_mem_usage=True, device_map="auto", load_in_4bit = True)
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+
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+
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+ PROMPT_DICT = {
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+ "prompt_input": (
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+ "以下に、あるタスクを説明する指示があり、それに付随する入力が更なる文脈を提供しています。"
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+ "リクエストを適切に完了するための回答を記述してください。\n\n"
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+ "### 指示:\n{instruction}\n\n### 入力:\n{input}\n\n### 応答:"
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+
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+ ),
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+ "prompt_no_input": (
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+ "以下に、あるタスクを説明する指示があります。"
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+ "リクエストを適切に完了するための回答を記述してください。\n\n"
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+ "### 指示:\n{instruction}\n\n### 応答:"
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+ ),
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+ }
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+
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+ def create_prompt(instruction, input=None):
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+ """
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+ Generates a prompt based on the given instruction and an optional input.
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+ If input is provided, it uses the 'prompt_input' template from PROMPT_DICT.
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+ If no input is provided, it uses the 'prompt_no_input' template.
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+
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+ Args:
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+ instruction (str): The instruction describing the task.
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+ input (str, optional): Additional input providing context for the task. Default is None.
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+
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+ Returns:
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+ str: The generated prompt.
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+ """
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+ if input:
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+ # Use the 'prompt_input' template when additional input is provided
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+ return PROMPT_DICT["prompt_input"].format(instruction=instruction, input=input)
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+ else:
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+ # Use the 'prompt_no_input' template when no additional input is provided
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+ return PROMPT_DICT["prompt_no_input"].format(instruction=instruction)
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+
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+ # Example usage
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+ instruction_example = "以下のトピックに関する詳細な情報を提供してください。"
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+ input_example = "東京工業大学の主なキャンパスについて教えてください"
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+ prompt = create_prompt(instruction_example, input_example)
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+
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+ input_ids = tokenizer.encode(
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+ prompt,
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+ add_special_tokens=False,
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+ return_tensors="pt"
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+ )
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+
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+ tokens = model.generate(
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+ input_ids.to(device=model.device),
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+ max_new_tokens=200,
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+ temperature=0.7,
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+ top_p=0.9,
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+ repetition_penalty=1.15,
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+ top_k=20,
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+ do_sample=True,
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+ )
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+
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+ out = tokenizer.decode(tokens[0], skip_special_tokens=True)
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+ print(out)
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+
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+ ```
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+
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+ ## Merge Details
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+ ### Merge Method
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+
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+ This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) and the SLERP merge method using [tokyotech-llm/Swallow-70b-instruct-hf](https://huggingface.co/tokyotech-llm/Swallow-70b-instruct-hf) as a base.
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+
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+ ### Models Merged
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+
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+ The following models were included in the merge:
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+ * [GOAT-AI/GOAT-70B-Storytelling](https://huggingface.co/GOAT-AI/GOAT-70B-Storytelling)
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+ * [dreamgen/opus-v0.5-70b](https://huggingface.co/dreamgen/opus-v0.5-70b)
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+ * [Doctor-Shotgun/lzlv-limarpv3-l2-70b](Doctor-Shotgun/lzlv-limarpv3-l2-70b)
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+ * [LoRA] [alac/Waxwing-Storytelling-70B-LoRA](https://huggingface.co/alac/Waxwing-Storytelling-70B-LoRA)
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+
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+ ### Configuration
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+
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+ The command example:
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+
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+ ```bash
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+ # please change the path and options according to your environment
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+ mergekit-mega --cuda Swallow-70b-RP.yml ~/text-generation-webui/models
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+ ```
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+
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+ The following YAML configuration was used to produce this model:
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+
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+ ```yaml
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+ models:
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+ - model: tokyotech-llm/Swallow-70b-instruct-hf
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+ # no parameters necessary for base model
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+ - model: nitky/Swallow-70b-NVE-RP
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+ parameters:
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+ density: 1
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+ weight:
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+ - filter: mlp
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+ value: 0.1
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+ - filter: self_attn
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+ value: 0.4
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+ - value: 0 # fallback for rest of tensors.
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+ merge_method: dare_ties
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+ base_model: tokyotech-llm/Swallow-70b-instruct-hf
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+ dtype: bfloat16
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+ tokenizer_source: union
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+ name: Swallow-70b-RP-base
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+ ---
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+ models:
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+ - model: tokyotech-llm/Swallow-70b-instruct-hf
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+ # no parameters necessary for base model
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+ - model: nitky/Swallow-70b-NVE-RP
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+ parameters:
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+ density: 1
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+ weight:
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+ - filter: mlp
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+ value: [0.4, 0.1, 0.4, 0.1, 0.4, 0.1, 0.4, 0.1, 0.1]
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+ - filter: self_attn
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+ value: [0.4, 0.4, 0.1, 0.4, 0.1, 0.4, 0.1, 0.4, 0.4]
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+ - value: 0 # fallback for rest of tensors.
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+ merge_method: dare_ties
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+ base_model: tokyotech-llm/Swallow-70b-instruct-hf
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+ dtype: bfloat16
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+ tokenizer_source: union
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+ name: Swallow-70b-RP-flavor
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+ ---
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+ slices:
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+ - sources:
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+ - model: Swallow-70b-RP-base
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+ layer_range: [0, 80]
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+ - model: Swallow-70b-RP-flavor
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+ layer_range: [0, 80]
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+ merge_method: slerp
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+ base_model: Swallow-70b-RP-base
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+ parameters:
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+ t: # model stabilization
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+ - filter: self_attn
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+ value: [0, 0.5, 0.3, 0.7, 1]
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+ - filter: mlp
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+ value: [1, 0.5, 0.7, 0.3, 0]
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+ - value: 0.5 # fallback for rest of tensors
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+ dtype: bfloat16
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+ name: Swallow-70b-RP
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+
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+ ```
config.json ADDED
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+ {
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+ "_name_or_path": "nitky/Swallow-70b-RP",
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+ "architectures": [
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+ "LlamaForCausalLM"
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+ ],
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+ "attention_bias": false,
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+ "attention_dropout": 0.0,
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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "hidden_act": "silu",
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+ "hidden_size": 8192,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 28672,
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+ "max_position_embeddings": 4096,
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+ "max_sequence_length": 4096,
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+ "model_type": "llama",
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+ "num_attention_heads": 64,
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+ "num_hidden_layers": 80,
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+ "num_key_value_heads": 8,
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+ "pad_token_id": 0,
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+ "pretraining_tp": 1,
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+ "rms_norm_eps": 1e-05,
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+ "rope_scaling": null,
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+ "rope_theta": 10000.0,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.36.2",
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+ "use_cache": true,
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+ "vocab_size": 43176
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+ }
mergekit_config.yml ADDED
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+ models:
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+ - model: tokyotech-llm/Swallow-70b-instruct-hf
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+ # no parameters necessary for base model
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+ - model: nitky/Swallow-70b-NVE-RP
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+ parameters:
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+ density: 1
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+ weight:
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+ - filter: mlp
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+ value: 0.1
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+ - filter: self_attn
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+ value: 0.4
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+ - value: 0 # fallback for rest of tensors.
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+ merge_method: dare_ties
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+ base_model: tokyotech-llm/Swallow-70b-instruct-hf
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+ dtype: bfloat16
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+ tokenizer_source: union
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+ name: Swallow-70b-RP-base
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+ ---
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+ models:
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+ - model: tokyotech-llm/Swallow-70b-instruct-hf
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+ # no parameters necessary for base model
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+ - model: nitky/Swallow-70b-NVE-RP
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+ parameters:
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+ density: 1
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+ weight:
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+ - filter: mlp
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+ value: [0.4, 0.1, 0.4, 0.1, 0.4, 0.1, 0.4, 0.1, 0.1]
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+ - filter: self_attn
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+ value: [0.4, 0.4, 0.1, 0.4, 0.1, 0.4, 0.1, 0.4, 0.4]
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+ - value: 0 # fallback for rest of tensors.
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+ merge_method: dare_ties
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+ base_model: tokyotech-llm/Swallow-70b-instruct-hf
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+ dtype: bfloat16
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+ tokenizer_source: union
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+ name: Swallow-70b-RP-flavor
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+ ---
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+ slices:
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+ - sources:
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+ - model: Swallow-70b-RP-base
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+ layer_range: [0, 80]
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+ - model: Swallow-70b-RP-flavor
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+ layer_range: [0, 80]
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+ merge_method: slerp
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+ base_model: Swallow-70b-RP-base
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+ parameters:
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+ t: # model stabilization
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+ - filter: self_attn
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+ value: [0, 0.5, 0.3, 0.7, 1]
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+ - filter: mlp
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+ value: [1, 0.5, 0.7, 0.3, 0]
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+ - value: 0.5 # fallback for rest of tensors
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+ dtype: bfloat16
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+ name: Swallow-70b-RP
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