Instructions to use bartowski/Tess-7B-v2.0-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 bartowski/Tess-7B-v2.0-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 bartowski/Tess-7B-v2.0-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf bartowski/Tess-7B-v2.0-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 bartowski/Tess-7B-v2.0-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf bartowski/Tess-7B-v2.0-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 bartowski/Tess-7B-v2.0-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf bartowski/Tess-7B-v2.0-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 bartowski/Tess-7B-v2.0-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf bartowski/Tess-7B-v2.0-GGUF:Q4_K_M

Use Docker

docker model run hf.co/bartowski/Tess-7B-v2.0-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use bartowski/Tess-7B-v2.0-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "bartowski/Tess-7B-v2.0-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": "bartowski/Tess-7B-v2.0-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/bartowski/Tess-7B-v2.0-GGUF:Q4_K_M

Ollama
How to use bartowski/Tess-7B-v2.0-GGUF with Ollama:
```
ollama run hf.co/bartowski/Tess-7B-v2.0-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use bartowski/Tess-7B-v2.0-GGUF with Docker Model Runner:
```
docker model run hf.co/bartowski/Tess-7B-v2.0-GGUF:Q4_K_M
```

Lemonade

How to use bartowski/Tess-7B-v2.0-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull bartowski/Tess-7B-v2.0-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.Tess-7B-v2.0-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

Chat template

by Handgun1773 - opened Mar 26, 2024

Discussion

Handgun1773

Mar 26, 2024

•

edited Mar 26, 2024

As in the original repo, the chat template in your GGUF doesn't match the one described in the original model card.
I made a PR in the original repo.

bartowski

Owner Mar 26, 2024

Thanks for the heads up! Let me know when it gets merged and I'll remake this with the proper template

algorithm

Mar 27, 2024

@Handgun1773 am I understanding this correctly, the line you changed in the original repo would be applied when running the model with llama.cpp?

Is the benefit of this that you can just simply use:

-p "write me a story"

As opposed to needing to add prefixes and all those flags?

Handgun1773

Apr 2, 2024

I don't know if llama.cpp take into account prompt templates from the GGUF files. I know ooba does when loading a GGUF with llama.cpp backend.

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