Instructions to use DiscoResearch/mixtral-7b-8expert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DiscoResearch/mixtral-7b-8expert with Transformers:

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

pipe = pipeline("text-generation", model="DiscoResearch/mixtral-7b-8expert", trust_remote_code=True)

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("DiscoResearch/mixtral-7b-8expert", trust_remote_code=True)
model = AutoModelForMultimodalLM.from_pretrained("DiscoResearch/mixtral-7b-8expert", trust_remote_code=True)

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use DiscoResearch/mixtral-7b-8expert with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DiscoResearch/mixtral-7b-8expert"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DiscoResearch/mixtral-7b-8expert",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/DiscoResearch/mixtral-7b-8expert

SGLang

How to use DiscoResearch/mixtral-7b-8expert 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 "DiscoResearch/mixtral-7b-8expert" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DiscoResearch/mixtral-7b-8expert",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "DiscoResearch/mixtral-7b-8expert" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DiscoResearch/mixtral-7b-8expert",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use DiscoResearch/mixtral-7b-8expert with Docker Model Runner:
```
docker model run hf.co/DiscoResearch/mixtral-7b-8expert
```

can this model run on cpu, I had a error when I test it on cpu, this with a error about should install flash_attn

#15

by wiseluke - opened Dec 16, 2023

Discussion

wiseluke

Dec 16, 2023

test code:
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

#model = AutoModelForCausalLM.from_pretrained("./model", low_cpu_mem_usage=True, device_map="cpu", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("./model", torch_dtype=torch.float16, device_map="cpu", trust_remote_code=True)
tok = AutoTokenizer.from_pretrained("./model").to("cpu")
x
= tok.encode("The mistral wind in is a phenomenon ", return_tensors="pt")
x = model.generate(x, max_new_tokens=128)
print(tok.batch_decode(x))

error message:
/home//.local/lib/python3.10/site-packages/torch/onnx/_internal/_beartype.py:30: UserWarning: module 'beartype.roar' has no attribute 'BeartypeDecorHintPep585DeprecationWarning'
warnings.warn(f"{e}")
Traceback (most recent call last):
File "/home//04_files/Model/mixtral/./test0.py", line 5, in
model = AutoModelForCausalLM.from_pretrained("./model", torch_dtype=torch.float16, device_map="cpu", trust_remote_code=True)
File "/home//.local/lib/python3.10/site-packages/transformers/models/auto/auto_factory.py", line 553, in from_pretrained
model_class = get_class_from_dynamic_module(
File "/home//.local/lib/python3.10/site-packages/transformers/dynamic_module_utils.py", line 488, in get_class_from_dynamic_module
final_module = get_cached_module_file(
File "/home//.local/lib/python3.10/site-packages/transformers/dynamic_module_utils.py", line 315, in get_cached_module_file
modules_needed = check_imports(resolved_module_file)
File "/home//.local/lib/python3.10/site-packages/transformers/dynamic_module_utils.py", line 180, in check_imports
raise ImportError(
ImportError: This modeling file requires the following packages that were not found in your environment: flash_attn. Run pip install flash_attn
I tried to install flash_attn ,but it cannot install succ without a cuda driver, so this model cannot work on cpu now?

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