Instructions to use hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-GGUF with Transformers:

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-GGUF", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-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 hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-GGUF:Q4_K_S
# Run inference directly in the terminal:
llama cli -hf hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-GGUF:Q4_K_S

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-GGUF:Q4_K_S
# Run inference directly in the terminal:
llama cli -hf hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-GGUF:Q4_K_S

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 hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-GGUF:Q4_K_S
# Run inference directly in the terminal:
./llama-cli -hf hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-GGUF:Q4_K_S

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 hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-GGUF:Q4_K_S
# Run inference directly in the terminal:
./build/bin/llama-cli -hf hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-GGUF:Q4_K_S

Use Docker

docker model run hf.co/hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-GGUF:Q4_K_S

LM Studio
Jan
Ollama
How to use hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-GGUF with Ollama:
```
ollama run hf.co/hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-GGUF:Q4_K_S
```
Unsloth Desktop
Docker Model Runner
How to use hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-GGUF with Docker Model Runner:
```
docker model run hf.co/hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-GGUF:Q4_K_S
```

Lemonade

How to use hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull hpcgroup/hpc-coder-v2-1.3b-Q4_K_S-GGUF:Q4_K_S

Run and chat with the model

lemonade run user.hpc-coder-v2-1.3b-Q4_K_S-GGUF-Q4_K_S

List all available models

lemonade list

Atomic Chat

hpc-coder-v2-1.3b-Q4_K_S-GGUF / imatrix.dat

daniellnichols

Upload imatrix.dat with huggingface_hub

86609dd verified about 2 years ago

History Blame Contribute Delete

6.12 MB

This file is stored with Xet . It is too big to display, but you can still download it.

Xet Pointer Details

( Raw pointer file )

Xet hash:: 79690eb76b6011a24a3169e1e8250163ed54da245777bc9ceba2bff4b413fb36
Size of remote file:: 6.12 MB
SHA256:: 1323d5f2358c872294ff0d30714229e30acd5894dfdab41c0e564f83c95d9ffb

Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.