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  • Developed by: taoki
  • License: apache-2.0
  • Finetuned from model : mistralai/Mistral-7B-Instruct-v0.3

Usage

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>
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Finetuned from

Datasets used to train taoki/Mistral-7B-Instruct-v0.3_lora_jmultiwoz-dolly-amenokaku-alpaca_jp_python