Instructions to use CultriX/MonaCeption-7B-SLERP-DPO with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use CultriX/MonaCeption-7B-SLERP-DPO with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("CultriX/MonaCeption-7B-SLERP-DPO", dtype="auto")

llama-cpp-python

How to use CultriX/MonaCeption-7B-SLERP-DPO with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="CultriX/MonaCeption-7B-SLERP-DPO",
	filename="monaception-7b-slerp-dpo.Q4_K_M.gguf",
)

output = llm(
	"Once upon a time,",
	max_tokens=512,
	echo=True
)
print(output)

Notebooks
Google Colab
Kaggle
Local Apps

llama.cpp

How to use CultriX/MonaCeption-7B-SLERP-DPO with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf CultriX/MonaCeption-7B-SLERP-DPO:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf CultriX/MonaCeption-7B-SLERP-DPO:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf CultriX/MonaCeption-7B-SLERP-DPO:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf CultriX/MonaCeption-7B-SLERP-DPO: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 CultriX/MonaCeption-7B-SLERP-DPO:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf CultriX/MonaCeption-7B-SLERP-DPO: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 CultriX/MonaCeption-7B-SLERP-DPO:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf CultriX/MonaCeption-7B-SLERP-DPO:Q4_K_M

Use Docker

docker model run hf.co/CultriX/MonaCeption-7B-SLERP-DPO:Q4_K_M

LM Studio
Jan
Ollama
How to use CultriX/MonaCeption-7B-SLERP-DPO with Ollama:
```
ollama run hf.co/CultriX/MonaCeption-7B-SLERP-DPO:Q4_K_M
```

Unsloth Studio new

How to use CultriX/MonaCeption-7B-SLERP-DPO 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 CultriX/MonaCeption-7B-SLERP-DPO 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 CultriX/MonaCeption-7B-SLERP-DPO to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for CultriX/MonaCeption-7B-SLERP-DPO to start chatting

Docker Model Runner
How to use CultriX/MonaCeption-7B-SLERP-DPO with Docker Model Runner:
```
docker model run hf.co/CultriX/MonaCeption-7B-SLERP-DPO:Q4_K_M
```

Lemonade

How to use CultriX/MonaCeption-7B-SLERP-DPO with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull CultriX/MonaCeption-7B-SLERP-DPO:Q4_K_M

Run and chat with the model

lemonade run user.MonaCeption-7B-SLERP-DPO-Q4_K_M

List all available models

lemonade list

YAML Metadata Warning:empty or missing yaml metadata in repo card

Check out the documentation for more information.

version https://git-lfs.github.com/spec/v1 oid sha256:70d5279d1ff8a2405f703524d96f7e4ab763861ec399570ffce6b41d68ed0a46 size 1176

Downloads last month: 11

Safetensors

Model size

7B params

Tensor type

F16

Inference Providers NEW

This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for CultriX/MonaCeption-7B-SLERP-DPO

Quantizations

1 model