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

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use pmysl/c4ai-command-r-plus-GGUF with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf pmysl/c4ai-command-r-plus-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf pmysl/c4ai-command-r-plus-GGUF:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf pmysl/c4ai-command-r-plus-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf pmysl/c4ai-command-r-plus-GGUF:Q4_K_M

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf pmysl/c4ai-command-r-plus-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf pmysl/c4ai-command-r-plus-GGUF:Q4_K_M

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf pmysl/c4ai-command-r-plus-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf pmysl/c4ai-command-r-plus-GGUF:Q4_K_M

Use Docker

docker model run hf.co/pmysl/c4ai-command-r-plus-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use pmysl/c4ai-command-r-plus-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "pmysl/c4ai-command-r-plus-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "pmysl/c4ai-command-r-plus-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/pmysl/c4ai-command-r-plus-GGUF:Q4_K_M

Ollama
How to use pmysl/c4ai-command-r-plus-GGUF with Ollama:
```
ollama run hf.co/pmysl/c4ai-command-r-plus-GGUF:Q4_K_M
```

Unsloth Studio

How to use pmysl/c4ai-command-r-plus-GGUF with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for pmysl/c4ai-command-r-plus-GGUF to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for pmysl/c4ai-command-r-plus-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for pmysl/c4ai-command-r-plus-GGUF to start chatting

Atomic Chat new
Docker Model Runner
How to use pmysl/c4ai-command-r-plus-GGUF with Docker Model Runner:
```
docker model run hf.co/pmysl/c4ai-command-r-plus-GGUF:Q4_K_M
```

Lemonade

How to use pmysl/c4ai-command-r-plus-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull pmysl/c4ai-command-r-plus-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.c4ai-command-r-plus-GGUF-Q4_K_M

List all available models

lemonade list

Does this use imatrix?

by nonetrix - opened Apr 8, 2024

Discussion

nonetrix

Apr 8, 2024

•

edited Apr 8, 2024

Seems imatrix can improve quants, does this use it? At 2 bits as expected it sometimes acts a bit strange, but I have seen other quants of similar sized models do better. I haven't tried 3 bits yet though might be able to squeeze it into 64GBs of RAM. Also, I think imatrix needs a dataset, ideally should be in all the languages that this model supports well. But, I imagine that it would greatly help with cases like this even with a lazy dataset

nonetrix

Apr 8, 2024

https://huggingface.co/dranger003/c4ai-command-r-plus-iMat.GGUF

nonetrix changed discussion status to closed Apr 8, 2024

pmysl

Owner Apr 8, 2024

These are regular quants (without imatrix)

Could you tell me which llama.cpp fork you use and what the SHA-256 hash of the weights is? There was an issue with F16 token embeddings, and I would like to make sure that this is not related to it

nonetrix

Apr 8, 2024

•

edited Apr 8, 2024

Well seems to always be periods a lot of the time it struggles with oddly, also seems to always pick similar words it will replace it with. Ignore the broken fonts that's a issue with my terminal with CJK languages not sure what it is

Anyway, as for the sum it's 47e139a57872a72096c05b043b1ec6c2f08451da7df0d84d45168708667b98f5 ./models/command-r-plus-Q2_K.gguf and I am running this https://github.com/ggerganov/llama.cpp/pull/6491 at commit d2924073ee9bdd600d22ded4e2d5fe30e69783a7

nonetrix

Apr 9, 2024

Tried Q3 big improvement and still have more spare memory than I thought I would

pmysl

Owner Apr 9, 2024

I have some early perplexity results on wikitext-2-raw and they seem to confirm this improvement

Test	PPL Value	Standard Deviation
Q2_K	5.7178	+/- 0.03418
Q3_K_L	4.6214	+/- 0.02629
Q4_K_M	4.4625	+/- 0.02522

Upload images, audio, and videos by dragging in the text input, pasting, or clicking here.

Tap or paste here to upload images

· Sign up or log in to comment