Instructions to use CohereLabs/c4ai-command-r-plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CohereLabs/c4ai-command-r-plus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="CohereLabs/c4ai-command-r-plus") 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") model = AutoModelForCausalLM.from_pretrained("CohereLabs/c4ai-command-r-plus", device_map="auto") 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-plus 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" # 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", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/CohereLabs/c4ai-command-r-plus
- SGLang
How to use CohereLabs/c4ai-command-r-plus 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" \ --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", "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" \ --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", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use CohereLabs/c4ai-command-r-plus with Docker Model Runner:
docker model run hf.co/CohereLabs/c4ai-command-r-plus
Update tool use template to new format
#46
by Rocketknight1 HF Staff - opened
Do not merge this yet! This is a currently experimental PR to test a new template format for tool use, to go with the new JSON schema standard for passing tools. Please see the updated docs for more info.
To try it out, you should install the latest version of transformers
Then, load the tokenizer and template from this PR branch:
from transformers import AutoTokenizer
from typing import List, Dict
tokenizer = AutoTokenizer.from_pretrained("CohereForAI/c4ai-command-r-plus", revision="pr/46")
def internet_search(query: str):
"""Returns a list of relevant document snippets for a textual query retrieved from the internet
Args:
query: Query to search the internet with
"""
pass
def directly_answer():
"""Calls a standard (un-augmented) AI chatbot to generate a response given the conversation history
"""
pass
conversation = [
{"role": "user", "content": "Whats the biggest penguin in the world?"}
]
tools = [internet_search, directly_answer]
new_tool_use_prompt = tokenizer.apply_chat_template(
conversation,
tools=tools,
chat_template="tool_use",
tokenize=False,
add_generation_prompt=True,
)
print(new_tool_use_prompt)
coherecode changed pull request status to merged