Instructions to use taoki/Mistral-7B-Instruct-v0.3_lora_jmultiwoz-dolly-amenokaku-alpaca_jp_python with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use taoki/Mistral-7B-Instruct-v0.3_lora_jmultiwoz-dolly-amenokaku-alpaca_jp_python with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="taoki/Mistral-7B-Instruct-v0.3_lora_jmultiwoz-dolly-amenokaku-alpaca_jp_python")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

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")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use taoki/Mistral-7B-Instruct-v0.3_lora_jmultiwoz-dolly-amenokaku-alpaca_jp_python with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "taoki/Mistral-7B-Instruct-v0.3_lora_jmultiwoz-dolly-amenokaku-alpaca_jp_python"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "taoki/Mistral-7B-Instruct-v0.3_lora_jmultiwoz-dolly-amenokaku-alpaca_jp_python",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/taoki/Mistral-7B-Instruct-v0.3_lora_jmultiwoz-dolly-amenokaku-alpaca_jp_python

SGLang

How to use taoki/Mistral-7B-Instruct-v0.3_lora_jmultiwoz-dolly-amenokaku-alpaca_jp_python with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "taoki/Mistral-7B-Instruct-v0.3_lora_jmultiwoz-dolly-amenokaku-alpaca_jp_python" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "taoki/Mistral-7B-Instruct-v0.3_lora_jmultiwoz-dolly-amenokaku-alpaca_jp_python",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "taoki/Mistral-7B-Instruct-v0.3_lora_jmultiwoz-dolly-amenokaku-alpaca_jp_python" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "taoki/Mistral-7B-Instruct-v0.3_lora_jmultiwoz-dolly-amenokaku-alpaca_jp_python",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use taoki/Mistral-7B-Instruct-v0.3_lora_jmultiwoz-dolly-amenokaku-alpaca_jp_python with Docker Model Runner:
```
docker model run hf.co/taoki/Mistral-7B-Instruct-v0.3_lora_jmultiwoz-dolly-amenokaku-alpaca_jp_python
```

Script Sharing

by Fayaz - opened Jun 21, 2025

Discussion

Fayaz

Jun 21, 2025

Hello Taoki,

I want to finetune this model but am stuck. Can you please share your script so that I can finetune this model or get some insight at least just the script not data. Thank You.

Best Regards
Fayaz Ali

taoki

Owner Jun 30, 2025

Hello, Fayaz Ali

Thank you for your interest.
I'm sorry I haven't updated much recently, but you can download the trained code at the following URI.
https://github.com/to-aoki/lora_finetuning

I hope it will be useful to you.

Best Regards
taoki

Fayaz

Jul 2, 2025

Thank You... Much Appreciated

Best Regards
Fayaz Ali

taoki changed discussion status to closed Jul 12, 2025

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