Update README.md

README.md

@@ -1,5 +1,8 @@
 ---
 license: other
+license_name: llama-3
+license_link: https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct/raw/main/LICENSE
+
 base_model: meta-llama/Meta-Llama-3-8B-Instruct
 tags:
 - generated_from_trainer
@@ -8,8 +11,45 @@ model-index:
   results: []
 ---
 
-<!-- This model card has been generated automatically according to the information the Trainer had access to. You
-should probably proofread and complete it, then remove this comment. -->
+<p align="center">
+  <img width=400 src="https://cdn-uploads.huggingface.co/production/uploads/64b63f8ad57e02621dc93c8b/kg3QjQOde0X743csGJT-f.png" alt="Suzume - a Japanese tree sparrow"/>
+</p>
+
+# Suzume
+
+This Suzume 8B, a Japanese finetune of Llama 3.
+
+Llama 3 has exhibited excellent performance on many English language benchmarks. 
+However, it also seemingly been finetuned on mostly English data, meaning that it will respond in English, even if prompted in Japanese.
+
+We have fine-tuned Llama 3 on almost 3,000 Japanese conversations meaning that this model has the smarts of Llama 3 but has the added ability to chat in Japanese.
+
+Please feel free to comment on this model and give us feedback in the Community tab!
+
+# How to use
+
+You can use the original trained model with vLLM like so:
+
+```python
+from vllm import LLM, SamplingParams
+
+sampling_params = SamplingParams(temperature=0.8, top_p=0.95)
+
+llm = LLM(model="lightblue/suzume-llama-3-8B-japanese")
+
+prompts = [
+  "東京のおすすめの観光スポットを教えて下さい",
+]
+
+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}")
+```
+
+# Training config
 
 [<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
 <details><summary>See axolotl config</summary>