--- license: apache-2.0 language: - ja --- # Tanuki-8B-Instruct ## Model Details - **Model type:** [Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B)-like pretrained Language Model - **Total seen tokens:** 280B |Params|Layers|Hidden size|Intermediate size|Attention Heads|KV Heads|Context length|Rope Theta| |:---:|:---:|:---:|:---:|:---:|:---:|:---:|:---:| |8b|32|4096|14336|32|8|8192|500000| ## Usage ```python import torch from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("hatakeyama-llm-team/Tanuki-8B-Instruct") model = AutoModelForCausalLM.from_pretrained("hatakeyama-llm-team/Tanuki-8B-Instruct", torch_dtype=torch.bfloat16).to('cuda') chat = [ {"role": "system", "content": "以下は、タスクを説明する指示と、文脈のある入力の組み合わせです。要求を適切に満たす応答を書きなさい。"}, {"role": "user", "content": "たぬきってなんですか?"}, ] tokenized_input = tokenizer.apply_chat_template(chat, add_generation_prompt=True, tokenize=True, return_tensors="pt").to(model.device) with torch.no_grad(): output = model.generate( tokenized_input, max_new_tokens=256, do_sample=True, temperature=0.7, repetition_penalty=1.05, )[0] print(tokenizer.decode(output)) ```

※生成時にtokenizer.apply_chat_templateではなくtokenizer.encode()を用いる場合は、文末にEOSトークンが挿入されないようadd_special_tokens=Falseを設定してください。
例: tokenizer.encode(input_text, add_special_tokens=False, return_tensors="pt")
tokenizer.apply_chat_templateの場合はadd_special_tokens=Falseがデフォルトのため問題ありません。

| Model Variant | | :--- | |**Instruction models**| | [hatakeyama-llm-team/Tanuki-8B-Instruct](https://huggingface.co/hatakeyama-llm-team/Tanuki-8B-Instruct) | | [hatakeyama-llm-team/Tanuki-8B-Instruct-without-DPO](https://huggingface.co/hatakeyama-llm-team/Tanuki-8B-Instruct-without-DPO) | |**Pre-trained models**| | [Tanuki-8B](https://huggingface.co/hatakeyama-llm-team/Tanuki-8B) | | [Tanuki-8B-Before-Context-Length-Extension](https://huggingface.co/hatakeyama-llm-team/Tanuki-8B-Before-Context-Length-Extension) |