Instructions to use TheBloke/Mistral-7B-Instruct-v0.1-GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TheBloke/Mistral-7B-Instruct-v0.1-GPTQ with Transformers:

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

pipe = pipeline("text-generation", model="TheBloke/Mistral-7B-Instruct-v0.1-GPTQ")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TheBloke/Mistral-7B-Instruct-v0.1-GPTQ")
model = AutoModelForCausalLM.from_pretrained("TheBloke/Mistral-7B-Instruct-v0.1-GPTQ", device_map="auto")
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 Settings

vLLM

How to use TheBloke/Mistral-7B-Instruct-v0.1-GPTQ with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TheBloke/Mistral-7B-Instruct-v0.1-GPTQ"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TheBloke/Mistral-7B-Instruct-v0.1-GPTQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/TheBloke/Mistral-7B-Instruct-v0.1-GPTQ

SGLang

How to use TheBloke/Mistral-7B-Instruct-v0.1-GPTQ 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 "TheBloke/Mistral-7B-Instruct-v0.1-GPTQ" \
    --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": "TheBloke/Mistral-7B-Instruct-v0.1-GPTQ",
		"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 "TheBloke/Mistral-7B-Instruct-v0.1-GPTQ" \
        --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": "TheBloke/Mistral-7B-Instruct-v0.1-GPTQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use TheBloke/Mistral-7B-Instruct-v0.1-GPTQ with Docker Model Runner:
```
docker model run hf.co/TheBloke/Mistral-7B-Instruct-v0.1-GPTQ
```

Mistral isn't supported yet

by abrehmaaan - opened Oct 6, 2023

Discussion

abrehmaaan

Oct 6, 2023

I am getting this error:
Traceback (most recent call last):
File "C:\Users\Administrator\Projects\localGPT\run_localGPT.py", line 267, in
main()
File "C:\Program Files\Python310\lib\site-packages\click\core.py", line 1157, in call
return self.main(*args, **kwargs)
File "C:\Program Files\Python310\lib\site-packages\click\core.py", line 1078, in main
rv = self.invoke(ctx)
File "C:\Program Files\Python310\lib\site-packages\click\core.py", line 1434, in invoke
return ctx.invoke(self.callback, **ctx.params)
File "C:\Program Files\Python310\lib\site-packages\click\core.py", line 783, in invoke
return __callback(*args, **kwargs)
File "C:\Users\Administrator\Projects\localGPT\run_localGPT.py", line 237, in main
qa = retrieval_qa_pipline(device_type, use_history, promptTemplate_type=model_type)
File "C:\Users\Administrator\Projects\localGPT\run_localGPT.py", line 132, in retrieval_qa_pipline
llm = load_model(device_type, model_id=MODEL_ID, model_basename=MODEL_BASENAME, LOGGING=logging)
File "C:\Users\Administrator\Projects\localGPT\run_localGPT.py", line 66, in load_model
model, tokenizer = load_quantized_model_qptq(model_id, model_basename, device_type, LOGGING)
File "C:\Users\Administrator\Projects\localGPT\load_models.py", line 95, in load_quantized_model_qptq
model = AutoGPTQForCausalLM.from_quantized(
File "C:\Program Files\Python310\lib\site-packages\auto_gptq\modeling\auto.py", line 79, in from_quantized
model_type = check_and_get_model_type(save_dir or model_name_or_path, trust_remote_code)
File "C:\Program Files\Python310\lib\site-packages\auto_gptq\modeling_utils.py", line 125, in check_and_get_model_type
raise TypeError(f"{config.model_type} isn't supported yet.")
TypeError: mistral isn't supported yet.

I am using localGPT repository from PromptEngineer.

abrehmaaan

Oct 6, 2023

@TheBloke Please help

TheBloke

Owner Oct 6, 2023

Yes, AutoGPTQ doesn't support Mistral GPTQ yet. You need to use Transformers GPTQ, or ExLlama.

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