Instructions to use CohereLabs/c4ai-command-a-03-2025 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CohereLabs/c4ai-command-a-03-2025 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="CohereLabs/c4ai-command-a-03-2025") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("CohereLabs/c4ai-command-a-03-2025") model = AutoModelForCausalLM.from_pretrained("CohereLabs/c4ai-command-a-03-2025") 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]:])) - Inference
- HuggingChat
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use CohereLabs/c4ai-command-a-03-2025 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "CohereLabs/c4ai-command-a-03-2025" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CohereLabs/c4ai-command-a-03-2025", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/CohereLabs/c4ai-command-a-03-2025
- SGLang
How to use CohereLabs/c4ai-command-a-03-2025 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 "CohereLabs/c4ai-command-a-03-2025" \ --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": "CohereLabs/c4ai-command-a-03-2025", "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 "CohereLabs/c4ai-command-a-03-2025" \ --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": "CohereLabs/c4ai-command-a-03-2025", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use CohereLabs/c4ai-command-a-03-2025 with Docker Model Runner:
docker model run hf.co/CohereLabs/c4ai-command-a-03-2025
Add this model to huggingchat
Please add this model to huggingchat, this model is highly considered one of the best because it does not have any censorship............
Here is the source code for huggingchat: https://github.com/huggingface/chat-ui
Hey @gmanskibidi , you can use Command A in our Hugging Face space (that uses chat-ui!) -- https://huggingface.co/spaces/CohereLabs/c4ai-command
Hey @gmanskibidi , you can use Command A in our Hugging Face space (that uses chat-ui!) -- https://huggingface.co/spaces/CohereLabs/c4ai-command
Nah, since this space requires zerogpu which requrires a subscription, its best to add this model to huggingchat anyway alongside the existing command r+.
@gmanskibidi our space does not require a subscription to be used.
but wouldn't it be better for you to add this model to huggingchat instead of requiring us to run it in your own private space? we might need to use other models alongside command a inside huggingchat as well.
Closing as huggingchat is no longer available.