Create README.md

README.md

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+---
+license: apache-2.0
+datasets:
+- OpenAssistant/oasst1
+- zetavg/ShareGPT-Processed
+- augmxnt/ultra-orca-boros-en-ja-v1
+language:
+- ja
+- en
+---
+
+
+<p align="center">
+  <img src="https://cdn-uploads.huggingface.co/production/uploads/64b63f8ad57e02621dc93c8b/3uLNwKHFwEgT2YQ-BGOiH.png" alt="drawing" width="600"/>
+</p>
+
+# How to use
+
+
+### Hugggingface
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+tokenizer = AutoTokenizer.from_pretrained("lightblue/karasu-7B-chat-plus")
+model = AutoModelForCausalLM.from_pretrained("lightblue/karasu-7B-chat-plus", torch_dtype=torch.bfloat16, device_map="auto")
+
+pipe = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+messages = [{"role": "system", "content": "あなたはAIアシスタントです。"}]
+messages.append({"role": "user", "content": "イギリスの首相は誰ですか？"})
+
+prompt = tokenizer.apply_chat_template(conversation=messages, add_generation_prompt=True, tokenize=False)
+
+pipe(prompt, max_new_tokens=100, do_sample=False, temperature=0.0, return_full_text=False)
+```
+
+
+### VLLM
+```python
+from vllm import LLM, SamplingParams
+
+sampling_params = SamplingParams(temperature=0.0, max_tokens=100)
+llm = LLM(model="lightblue/karasu-7B-chat-plus")
+
+messages = [{"role": "system", "content": "あなたはAIアシスタントです。"}]
+messages.append({"role": "user", "content": "イギリスの首相は誰ですか？"})
+prompt = llm.llm_engine.tokenizer.apply_chat_template(conversation=messages, add_generation_prompt=True, tokenize=False)
+prompts = [prompt]
+
+outputs = llm.generate(prompts, sampling_params)
+for output in outputs:
+    prompt = output.prompt
+    generated_text = output.outputs[0].text
+    print(f"Prompt: {prompt!r}, Generated text: {generated_text!r}")
+```
+
+
+
+# Base checkpoint
+[lightblue/karasu-7B](https://huggingface.co/lightblue/karasu-7B)
+
+# Training datasets (total ~7B)
+The same as the 'plus' checkpoint, but with about 6K refusals ("申し訳ありませんが、。。。") filtered out from the category dataset 
+* Lightblue's suite of Kujira datasets (unreleased)
+* Lightblue's own question-based datasets (unreleased)
+* Lightblue's own category-based datasets (unreleased)
+* [OASST](https://huggingface.co/datasets/OpenAssistant/oasst1) (Japanese chats only)
+* [ShareGPT](https://huggingface.co/datasets/zetavg/ShareGPT-Processed) (Japanese chats only)
+* [augmxnt/ultra-orca-boros-en-ja-v1](https://huggingface.co/datasets/augmxnt/ultra-orca-boros-en-ja-v1) (['airoboros', 'slimorca', 'ultrafeedback', 'airoboros_ja_new'] only)
+
+# Developed by
+
+<a href="https://www.lightblue-tech.com">
+<img src="https://www.lightblue-tech.com/wp-content/uploads/2021/10/LBlogo-scaled.jpg" alt="Lightblue technology logo" width="400"/>
+</a>
+
+### Engineers
+Peter Devine
+
+Sho Higuchi
+
+### Advisors
+Yuuki Yamanaka 
+
+Atom Sonoda
+
+### Dataset evaluator
+Renju Aoki