Update README.md

README.md

@@ -9,4 +9,29 @@ widget:
 - text: "自然言語処理とは何か"
 ---
 
-llm-jp's [llm-jp-1.3b-v1.0](https://huggingface.co/llm-jp/llm-jp-1.3b-v1.0) model fine-tuned on the Japanese examples from Cohere's [aya dataset](https://huggingface.co/datasets/CohereForAI/aya_dataset)
+# llm-jp-1.3b-v1.0-aya
+llm-jp's [llm-jp-1.3b-v1.0](https://huggingface.co/llm-jp/llm-jp-1.3b-v1.0) model fine-tuned on the Japanese examples from Cohere's [aya dataset](https://huggingface.co/datasets/CohereForAI/aya_dataset)
+
+| Model                             | [llm-jp-eval AVG](https://wandb.ai/wandb-japan/llm-leaderboard/reports/Nejumi-LLM-Leaderboard-Evaluating-Japanese-Language-Proficiency--Vmlldzo2MzU3NzIy#deep-dive-into-llm-jp-eval) |
+|-----------------------------------|---------|
+| kcoopermiller/llm-jp-1.3b-v1.0-aya     | **0.0698**    |
+| llm-jp/llm-jp-1.3b-v1.0 | 0.047   |
+
+## How to use
+```python
+import torch
+from transformers import AutoTokenizer, AutoModelForCausalLM
+tokenizer = AutoTokenizer.from_pretrained("kcoopermiller/llm-jp-1.3b-v1.0-aya")
+model = AutoModelForCausalLM.from_pretrained("kcoopermiller/llm-jp-1.3b-v1.0-aya", device_map="auto")
+text = "自然言語処理とは何か"
+tokenized_input = tokenizer.encode(text, add_special_tokens=False, return_tensors="pt").to(model.device)
+with torch.no_grad():
+    output = model.generate(
+        tokenized_input,
+        max_new_tokens=20,
+        do_sample=True,
+        top_p=0.90,
+        temperature=0.7,
+    )[0]
+print(tokenizer.decode(output))
+```