Instructions to use PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed with Pruna AI:

from pruna import PrunaModel
model = PrunaModel.from_pretrained("PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed")

llama-cpp-python

How to use PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed",
	filename="jpacifico/Chocolatine-14B-Instruct-DPO-v1.2.Q2_K.gguf",
)

llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed 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 PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed: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 PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed: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 PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed:Q4_K_M

Use Docker

docker model run hf.co/PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed:Q4_K_M

LM Studio
Jan
Ollama
How to use PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed with Ollama:
```
ollama run hf.co/PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed:Q4_K_M
```

Unsloth Studio

How to use PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed 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 PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed 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 PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed to start chatting

Atomic Chat new
Docker Model Runner
How to use PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed with Docker Model Runner:
```
docker model run hf.co/PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed:Q4_K_M
```

Lemonade

How to use PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull PrunaAI/jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed:Q4_K_M

Run and chat with the model

lemonade run user.jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed-Q4_K_M

List all available models

lemonade list

jpacifico-Chocolatine-14B-Instruct-DPO-v1.2-GGUF-smashed / jpacifico /Chocolatine-14B-Instruct-DPO-v1.2.Q4_1.gguf

sharpenb

Upload jpacifico/Chocolatine-14B-Instruct-DPO-v1.2.Q4_1.gguf with huggingface_hub

1c72230 verified over 1 year ago

Download

History Blame

8.76 GB

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:: 70c8ad21c3a418be303eba7fe1494fc27f28c85d0d52a1eb949feda9c3c18af0
Size of remote file:: 8.76 GB
SHA256:: b7ef9032424b2459892adcbba1088f35cf1505f51d2c9cdaa4f71d274c51e612

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