Instructions to use Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix", dtype="auto")

llama-cpp-python

How to use Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix with llama-cpp-python:

# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix",
	filename="BuRPInfinity_9B-F16.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 Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix with llama.cpp:

Install from brew

brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix:Q4_K_M

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix:Q4_K_M
# Run inference directly in the terminal:
llama-cli -hf Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix: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 Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix: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 Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix:Q4_K_M

Use Docker

docker model run hf.co/Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix:Q4_K_M

LM Studio
Jan
Ollama
How to use Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix with Ollama:
```
ollama run hf.co/Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix:Q4_K_M
```

Unsloth Studio

How to use Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix 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 Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix 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 Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix to start chatting

Docker Model Runner
How to use Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix with Docker Model Runner:
```
docker model run hf.co/Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix:Q4_K_M
```

Lemonade

How to use Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix:Q4_K_M

Run and chat with the model

lemonade run user.BuRPInfinity_9B-GGUF-IQ-Imatrix-Q4_K_M

List all available models

lemonade list

This repository hosts GGUF-IQ-Imatrix quants for jeiku/BuRPInfinity_9B.

Thanks @jeiku for merging this!

This is an experimental model. Feedback is appreciated as always.

Steps:

Base⇢ GGUF(F16)⇢ Imatrix-Data(F16)⇢ GGUF(Imatrix-Quants)

Using the latest llama.cpp at the time.

    quantization_options = [
        "Q4_K_M", "Q4_K_S", "IQ4_XS", "Q5_K_M", "Q5_K_S",
        "Q6_K", "Q8_0", "IQ3_M", "IQ3_S", "IQ3_XXS"
    ]

BuRPInfinity_9B

This is a merge of pre-trained language models created using mergekit.

Merge Details

Merge Method

This model was merged using the passthrough merge method.

Models Merged

The following models were included in the merge:

Configuration

The following YAML configuration was used to produce this model:

slices:
  - sources:
      - model: Endevor/InfinityRP-v1-7B
        layer_range: [0, 20]
  - sources:
      - model: ChaoticNeutrals/BuRP_7B
        layer_range: [12, 32]
merge_method: passthrough
dtype: float16

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GGUF

Model size

9B params

Architecture

llama

Hardware compatibility

3-bit

4-bit

5-bit

6-bit

8-bit

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Model tree for Lewdiculous/BuRPInfinity_9B-GGUF-IQ-Imatrix

ChaoticNeutrals/BuRP_7B

Endevor/InfinityRP-v1-7B

Merge model

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