Instructions to use brittlewis12/distilabeled-Marcoro14-7B-slerp-full-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 brittlewis12/distilabeled-Marcoro14-7B-slerp-full-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 brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf brittlewis12/distilabeled-Marcoro14-7B-slerp-full-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 brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf brittlewis12/distilabeled-Marcoro14-7B-slerp-full-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 brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf brittlewis12/distilabeled-Marcoro14-7B-slerp-full-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 brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF:Q4_K_M

Use Docker

docker model run hf.co/brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF:Q4_K_M

Ollama
How to use brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF with Ollama:
```
ollama run hf.co/brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF:Q4_K_M
```

Unsloth Studio

How to use brittlewis12/distilabeled-Marcoro14-7B-slerp-full-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 brittlewis12/distilabeled-Marcoro14-7B-slerp-full-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 brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF to start chatting

Docker Model Runner
How to use brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF with Docker Model Runner:
```
docker model run hf.co/brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF:Q4_K_M
```

Lemonade

How to use brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.distilabeled-Marcoro14-7B-slerp-full-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

distilabeled-Marcoro14-7B-slerp-full GGUF

Original model: distilabeled-Marcoro14-7B-slerp-full Model creator: Argilla

This repo contains GGUF format model files for Argilla’s distilabeled-Marcoro14-7B-slerp-full.

As described on the original model card:

This model is a new DPO fine-tune of our new open dataset argilla/distilabel-intel-orca-dpo-pairs, on the mlabonne/Marcoro14-7B-slerp model. You can find more information of the "distilabeled" dataset used at this repo argilla/distilabeled-Hermes-2.5-Mistral-7B, and visit distilabel.

The difference between this model and argilla/distilabeled-Marcoro14-7B-slerp is that this model has been fine-tuned for a whole epoch instead instead of 200 steps, so it has seen the whole dataset.

What is GGUF?

GGUF is a file format for representing AI models. It is the third version of the format, introduced by the llama.cpp team on August 21st 2023. It is a replacement for GGML, which is no longer supported by llama.cpp. Converted using llama.cpp build 1879 (revision 3e5ca79)

Prompt template: Unknown

{{prompt}}

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Original Model Evaluations:

Model	AGIEval	GPT4ALL	TruthfulQA	Bigbench	Average
argilla/distilabeled-Marcoro14-7B-slerp-full	45.17	76.59	64.68	48.15	58.65
argilla/distilabeled-Marcoro14-7B-slerp	45.4	76.47	65.46	47.19	58.63
Marcoro14-7B-slerp	44.66	76.24	64.15	45.64	57.67
argilla/distilabeled-Hermes-2.5-Mistral-7B	44.64	73.35	55.96	42.21	54.04

Downloads last month: 36

GGUF

Model size

7B params

Architecture

llama

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

Model tree for brittlewis12/distilabeled-Marcoro14-7B-slerp-full-GGUF

Base model

argilla/distilabeled-Marcoro14-7B-slerp-full

Quantized

(5)

this model

brittlewis12
/

distilabeled-Marcoro14-7B-slerp-full-GGUF