Instructions to use tensorblock/Ahma-7B-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use tensorblock/Ahma-7B-GGUF with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="tensorblock/Ahma-7B-GGUF",
	filename="Ahma-7B-Q2_K.gguf",
)

llm.create_chat_completion(
	messages = [
		{
			"role": "user",
			"content": "What is the capital of France?"
		}
	]
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use tensorblock/Ahma-7B-GGUF with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf tensorblock/Ahma-7B-GGUF:Q2_K
# Run inference directly in the terminal:
llama-cli -hf tensorblock/Ahma-7B-GGUF:Q2_K

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf tensorblock/Ahma-7B-GGUF:Q2_K
# Run inference directly in the terminal:
llama-cli -hf tensorblock/Ahma-7B-GGUF:Q2_K

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 tensorblock/Ahma-7B-GGUF:Q2_K
# Run inference directly in the terminal:
./llama-cli -hf tensorblock/Ahma-7B-GGUF:Q2_K

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 tensorblock/Ahma-7B-GGUF:Q2_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf tensorblock/Ahma-7B-GGUF:Q2_K

Use Docker

docker model run hf.co/tensorblock/Ahma-7B-GGUF:Q2_K

LM Studio
Jan

vLLM

How to use tensorblock/Ahma-7B-GGUF with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/tensorblock/Ahma-7B-GGUF:Q2_K

Ollama
How to use tensorblock/Ahma-7B-GGUF with Ollama:
```
ollama run hf.co/tensorblock/Ahma-7B-GGUF:Q2_K
```

Unsloth Studio

How to use tensorblock/Ahma-7B-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 tensorblock/Ahma-7B-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 tensorblock/Ahma-7B-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for tensorblock/Ahma-7B-GGUF to start chatting

Docker Model Runner
How to use tensorblock/Ahma-7B-GGUF with Docker Model Runner:
```
docker model run hf.co/tensorblock/Ahma-7B-GGUF:Q2_K
```

Lemonade

How to use tensorblock/Ahma-7B-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull tensorblock/Ahma-7B-GGUF:Q2_K

Run and chat with the model

lemonade run user.Ahma-7B-GGUF-Q2_K

List all available models

lemonade list

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:e0bc7415de81361994923340a7990417d65beebb4ffd05235079c9ae31f20739
-size 3763153664

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:7e785f22c063727b046f12ef583c79f813d650474eb5684e69d679c023347711
-size 3114347264

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:17c6acb5ee871eb18748fca0d5c0ac660c8257c0f530c0fbd5c4bf0917aee4a4
-size 4009396992

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:2f9810ff749b1c6da573321ae82ace0d4b371aacbcdf5d5504a368bb35c6b19c
-size 4264594176

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:0a1c7b9505af82d83560df367d09649755dca2725359e1421182b0baa1e36a12
-size 4040329984

tensorblock
/

Ahma-7B-GGUF

Keep Q2_K/Q3_K_M gguf only