Text Generation
Transformers
Safetensors
clover_moe
clover
mixture-of-experts
diffusion
custom-code
conversational
custom_code
Instructions to use Diffuspace/Clover-35B-A3B-Preview with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Diffuspace/Clover-35B-A3B-Preview with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Diffuspace/Clover-35B-A3B-Preview", trust_remote_code=True) messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("Diffuspace/Clover-35B-A3B-Preview", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Diffuspace/Clover-35B-A3B-Preview with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Diffuspace/Clover-35B-A3B-Preview" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Diffuspace/Clover-35B-A3B-Preview", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Diffuspace/Clover-35B-A3B-Preview
- SGLang
How to use Diffuspace/Clover-35B-A3B-Preview 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 "Diffuspace/Clover-35B-A3B-Preview" \ --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": "Diffuspace/Clover-35B-A3B-Preview", "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 "Diffuspace/Clover-35B-A3B-Preview" \ --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": "Diffuspace/Clover-35B-A3B-Preview", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Diffuspace/Clover-35B-A3B-Preview with Docker Model Runner:
docker model run hf.co/Diffuspace/Clover-35B-A3B-Preview
FP8 or INT4?
#3
by garrettkolson - opened
This looks awesome! Would it be possible to get an FP8 or INT4 quant for use with vLLM?
INT4 and FP4 to start with okay?
Yes, those would be great! Thank you!
Thank you!