Instructions to use CohereLabs/c4ai-command-r-v01-4bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use CohereLabs/c4ai-command-r-v01-4bit with Transformers:

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

pipe = pipeline("text-generation", model="CohereLabs/c4ai-command-r-v01-4bit", trust_remote_code=True)
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("CohereLabs/c4ai-command-r-v01-4bit", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("CohereLabs/c4ai-command-r-v01-4bit", trust_remote_code=True)
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 CohereLabs/c4ai-command-r-v01-4bit with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "CohereLabs/c4ai-command-r-v01-4bit"
# 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-r-v01-4bit",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/CohereLabs/c4ai-command-r-v01-4bit

SGLang

How to use CohereLabs/c4ai-command-r-v01-4bit 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-r-v01-4bit" \
    --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-r-v01-4bit",
		"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-r-v01-4bit" \
        --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-r-v01-4bit",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use CohereLabs/c4ai-command-r-v01-4bit with Docker Model Runner:
```
docker model run hf.co/CohereLabs/c4ai-command-r-v01-4bit
```

vLLM Deploy

#10

by shacotustra - opened Jul 23, 2024

Discussion

shacotustra

Jul 23, 2024

How to delpoy that model in vLLM?

Traceback (most recent call last):
[rank0]: File "/llms/com_r_trial.py", line 12, in
[rank0]: llm = LLM(model="/llms/c4ai-command-r-v01-4bit", quantization = 'bitsandbytes', load_format = 'bitsandbytes')
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/entrypoints/llm.py", line 155, in init
[rank0]: self.llm_engine = LLMEngine.from_engine_args(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/engine/llm_engine.py", line 441, in from_engine_args
[rank0]: engine = cls(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/engine/llm_engine.py", line 251, in init
[rank0]: self.model_executor = executor_class(
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/executor/executor_base.py", line 47, in init
[rank0]: self._init_executor()
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/executor/gpu_executor.py", line 36, in _init_executor
[rank0]: self.driver_worker.load_model()
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/worker/worker.py", line 139, in load_model
[rank0]: self.model_runner.load_model()
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/worker/model_runner.py", line 682, in load_model
[rank0]: self.model = get_model(model_config=self.model_config,
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/model_executor/model_loader/init.py", line 21, in get_model
[rank0]: return loader.load_model(model_config=model_config,
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/model_executor/model_loader/loader.py", line 828, in load_model
[rank0]: model = _initialize_model(model_config, self.load_config,
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/model_executor/model_loader/loader.py", line 109, in _initialize_model
[rank0]: quant_config = _get_quantization_config(model_config, load_config)
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/model_executor/model_loader/loader.py", line 50, in _get_quantization_config
[rank0]: quant_config = get_quant_config(model_config, load_config)
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/model_executor/model_loader/weight_utils.py", line 130, in get_quant_config
[rank0]: return quant_cls.from_config(hf_quant_config)
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/model_executor/layers/quantization/bitsandbytes.py", line 52, in from_config
[rank0]: adapter_name = cls.get_from_keys(config, ["adapter_name_or_path"])
[rank0]: File "/usr/local/lib/python3.10/dist-packages/vllm/model_executor/layers/quantization/base_config.py", line 87, in get_from_keys
[rank0]: raise ValueError(f"Cannot find any of {keys} in the model's "
[rank0]: ValueError: Cannot find any of ['adapter_name_or_path'] in the model's quantization config.

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