Instructions to use dranger003/c4ai-command-r-plus-iMat.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 dranger003/c4ai-command-r-plus-iMat.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 dranger003/c4ai-command-r-plus-iMat.GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf dranger003/c4ai-command-r-plus-iMat.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 dranger003/c4ai-command-r-plus-iMat.GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf dranger003/c4ai-command-r-plus-iMat.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 dranger003/c4ai-command-r-plus-iMat.GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf dranger003/c4ai-command-r-plus-iMat.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 dranger003/c4ai-command-r-plus-iMat.GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf dranger003/c4ai-command-r-plus-iMat.GGUF:Q4_K_M

Use Docker

docker model run hf.co/dranger003/c4ai-command-r-plus-iMat.GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use dranger003/c4ai-command-r-plus-iMat.GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "dranger003/c4ai-command-r-plus-iMat.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": "dranger003/c4ai-command-r-plus-iMat.GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/dranger003/c4ai-command-r-plus-iMat.GGUF:Q4_K_M

Ollama
How to use dranger003/c4ai-command-r-plus-iMat.GGUF with Ollama:
```
ollama run hf.co/dranger003/c4ai-command-r-plus-iMat.GGUF:Q4_K_M
```

Unsloth Studio

How to use dranger003/c4ai-command-r-plus-iMat.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 dranger003/c4ai-command-r-plus-iMat.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 dranger003/c4ai-command-r-plus-iMat.GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for dranger003/c4ai-command-r-plus-iMat.GGUF to start chatting

Docker Model Runner
How to use dranger003/c4ai-command-r-plus-iMat.GGUF with Docker Model Runner:
```
docker model run hf.co/dranger003/c4ai-command-r-plus-iMat.GGUF:Q4_K_M
```

Lemonade

How to use dranger003/c4ai-command-r-plus-iMat.GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull dranger003/c4ai-command-r-plus-iMat.GGUF:Q4_K_M

Run and chat with the model

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

List all available models

lemonade list

Atomic Chat

Can't load the model into llama.cpp

by ikci - opened Apr 8, 2024

Discussion

ikci

Apr 8, 2024

•

edited Apr 8, 2024

I'm getting the following error:

llama_model_load: error loading model: done_getting_tensors: wrong number of tensors; expected 642, got 514
llama_load_model_from_file: failed to load model
llama_init_from_gpt_params: error: failed to load model '../models/ggml-c4ai-command-r-plus-104b-iq2_xxs.gguf'
{"tid":"140149869789376","timestamp":1712538037,"level":"ERR","function":"load_model","line":681,"msg":"unable to load model","model":"../models/ggml-c4ai-command-r-plus-104b-iq2_xxs.gguf"}```

When trying to run the model with this command `./server -m ../models/ggml-c4ai-command-r-plus-104b-iq2_xxs.gguf -ngl 20 --host 
0.0.0.0 -c 4096`

Other AI models work properly but the 3 different GGUF sizes I tried downloading from this repo don't. I'm using latest git commit of llama.cpp.
Any idea what is causing it or if it can be fixed?

ikci

Apr 8, 2024

Nvm apparently the support isn't merged in yet.

ikci changed discussion status to closed Apr 8, 2024

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