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

Libraries

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

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

pipe = pipeline("text-generation", model="CohereLabs/c4ai-command-r-plus-4bit")
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-plus-4bit")
model = AutoModelForCausalLM.from_pretrained("CohereLabs/c4ai-command-r-plus-4bit")
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

vLLM

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

Use Docker

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

SGLang

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

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

Unexpected Random Outputs

by langematan - opened Apr 7, 2024

Discussion

langematan

Apr 7, 2024

encountering an unexpected and issue with this version. Specifically, I've been following the implementation example provided in the model card directly, anticipating a smooth initiation. However, the model's outputs have been random and disjointed, contrary to the coherent outputs in huggingface space.
what am i doing wrong ?

ahmetustun

Apr 7, 2024

Hi, are you using the latest transformers commit from the source? This needs to be installed as pip install 'git+https://github.com/huggingface/transformers.git

langematan

Apr 7, 2024

I'm using transformers ==4.39.3

ahmetustun

Apr 7, 2024

This model requires transformers installation from the source repo since there are modifications not included in 4.39.3

ahmetustun changed discussion status to closed Apr 8, 2024

fbjr

Apr 8, 2024

Are you sure this isn't related to the tokenizer.json differences between the 4bit bnb and the original cohere model? we're seeing this cause issues downstream in other conversions too.

see: https://huggingface.co/CohereForAI/c4ai-command-r-plus/discussions/15
and: https://github.com/huggingface/transformers/pull/30027

ahmetustun

Apr 8, 2024

•

edited Apr 8, 2024

hi @fbjr , the difference between tokenizers.json is unicode encoding in the command-r-plus. Also<|END_OF_TURN_TOKEN|> token is also set as special in 4bit because it is used as eos_token, which is also overwritten in the original tokenizer (command-r-plus) as well. Therefore, tokenizers should work the same. I can not reproduce the issue that @langematan mentioned.

fbjr

Apr 8, 2024

Thanks @ahmetustun !

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