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- Steps = 50004step
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ license: apache-2.0
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+ license_name: tongyi-qianwen-license-agreement
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+ license_link: >-
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+ https://github.com/QwenLM/Qwen/blob/main/Tongyi%20Qianwen%20LICENSE%20AGREEMENT
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+ datasets:
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+ - oscar-corpus/OSCAR-2301
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+ - mc4
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+ language:
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+ - ja
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+ ---
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+
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+ <p align="center">
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+ <img src="https://cdn-uploads.huggingface.co/production/uploads/64c8a2e01c25d2c581a381c1/9CbN4lDGU42c-7DmK_mGM.png" alt="drawing" width="600"/>
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+ </p>
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+
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+ TinyLlama + Japanese pre-training (50,004 steps)
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+
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+ # How to use
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+
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+
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+ ### Hugggingface
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+ ```python
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+ from transformers import AutoTokenizer, AutoModelForCausalLM
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+ import torch
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+
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+ tokenizer = AutoTokenizer.from_pretrained("lightblue/karasu-1.1B")
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+ model = AutoModelForCausalLM.from_pretrained("lightblue/karasu-1.1B", torch_dtype=torch.bfloat16, device_map="auto")
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+
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+ pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
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+
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+ messages = [{"role": "system", "content": "あなたはAIアシスタントです。"}]
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+ messages.append({"role": "user", "content": "イギリスの首相は誰ですか?"})
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+
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+ prompt = tokenizer.apply_chat_template(conversation=messages, add_generation_prompt=True, tokenize=False)
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+
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+ pipe(prompt, max_new_tokens=100, do_sample=False, temperature=0.0, return_full_text=False)
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+ ```
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+
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+
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+ ### VLLM
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+ ```python
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+ from vllm import LLM, SamplingParams
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+
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+ sampling_params = SamplingParams(temperature=0.0, max_tokens=100)
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+ llm = LLM(model="lightblue/karasu-1.1B")
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+
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+ messages = [{"role": "system", "content": "あなたはAIアシスタントです。"}]
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+ messages.append({"role": "user", "content": "イギリスの首相は誰ですか?"})
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+ prompt = llm.llm_engine.tokenizer.apply_chat_template(conversation=messages, add_generation_prompt=True, tokenize=False)
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+ prompts = [prompt]
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+
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+ outputs = llm.generate(prompts, sampling_params)
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+ for output in outputs:
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+ prompt = output.prompt
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+ generated_text = output.outputs[0].text
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+ print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
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+ ```
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+
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+
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+
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+ # Base checkpoint
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+ [Qwen/Qwen-14B-Chat](TinyLlama/TinyLlama-1.1B-intermediate-step-715k-1.5T)
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+
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+ # Training datasets (total ~3B)
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+ A filtered then sampled set from
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+ * OSCAR (Japanese)
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+ * mC4 (Japanese)
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+
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+ # Developed by
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+
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+ <a href="https://www.lightblue-tech.com">
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+ <img src="https://www.lightblue-tech.com/wp-content/uploads/2023/08/color_%E6%A8%AA%E5%9E%8B-1536x469.png" alt="Lightblue technology logo" width="400"/>
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+ </a>
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+
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+ ### Engineers
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+ Peter Devine
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+
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+ Sho Higuchi
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+
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+ ### Advisors
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+ Yuuki Yamanaka
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+
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+ Atom Sonoda
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+
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+ ### Project manager
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+ Shunichi Taniguchi
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+
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+ Tomioka Wataru
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+
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+ ### Dataset evaluator
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+ Renju Aoki