taoki
/

Mistral-7B-Instruct-v0.3_lora_jmultiwoz-dolly-amenokaku-alpaca_jp_python

@@ -1,199 +1,78 @@
 ---
-library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
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 ---
+language:
+- ja
+license: apache-2.0
+tags:
+- text-generation-inference
+- transformers
+- trl
+- mistral
+datasets:
+- sakusakumura/databricks-dolly-15k-ja-scored
+- nu-dialogue/jmultiwoz
+- kunishou/amenokaku-code-instruct
+- HachiML/alpaca_jp_python
+base_model: mistralai/Mistral-7B-Instruct-v0.3
 ---
+# Uploaded  model
+- **Developed by:** taoki
+- **License:** apache-2.0
+- **Finetuned from model :** mistralai/Mistral-7B-Instruct-v0.3
+# Usage
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+tokenizer = AutoTokenizer.from_pretrained(
+  "taoki/Mistral-7B-Instruct-v0.3_lora_jmultiwoz-dolly-amenokaku-alpaca_jp_python"
+)
+model = AutoModelForCausalLM.from_pretrained(
+  "taoki/Mistral-7B-Instruct-v0.3_lora_jmultiwoz-dolly-amenokaku-alpaca_jp_python"
+)
+if torch.cuda.is_available():
+    model = model.to("cuda")
+prompt="""[INST] OpenCVを用いて定点カメラから画像を保存するコードを示してください。 [/INST]"""
+input_ids = tokenizer(prompt, return_tensors="pt").to(model.device)
+outputs = model.generate(
+    **input_ids,
+    max_new_tokens=512,
+    do_sample=True,
+    top_p=0.9,
+    temperature=0.2,
+    repetition_penalty=1.1,
+)
+print(tokenizer.decode(outputs[0]))
+```
+# Output
+````
+<s>[INST] OpenCVを用いて定点カメラから画像を保存するコードを示してください。 [/INST]```python
+import cv2
+# カメラの設定
+cap = cv2.VideoCapture(0)
+# フレーム数
+frame_count = 10
+# 画像の保存
+for i in range(frame_count):
+    # フレームの取得
+    ret, frame = cap.read()
+    # 画像の保存
+    cv2.imwrite('image_{}.jpg'.format(i), frame)
+# カメラの終了
+cap.release()
+```</s>
+````