Instructions to use Lewdiculous/SLIDE-v2-GGUF-IQ-Imatrix with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Lewdiculous/SLIDE-v2-GGUF-IQ-Imatrix with Transformers:

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Lewdiculous/SLIDE-v2-GGUF-IQ-Imatrix", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use Lewdiculous/SLIDE-v2-GGUF-IQ-Imatrix 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 Lewdiculous/SLIDE-v2-GGUF-IQ-Imatrix:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Lewdiculous/SLIDE-v2-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 serve -hf Lewdiculous/SLIDE-v2-GGUF-IQ-Imatrix:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf Lewdiculous/SLIDE-v2-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/SLIDE-v2-GGUF-IQ-Imatrix:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf Lewdiculous/SLIDE-v2-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/SLIDE-v2-GGUF-IQ-Imatrix:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf Lewdiculous/SLIDE-v2-GGUF-IQ-Imatrix:Q4_K_M

Use Docker

docker model run hf.co/Lewdiculous/SLIDE-v2-GGUF-IQ-Imatrix:Q4_K_M

LM Studio
Jan
Ollama
How to use Lewdiculous/SLIDE-v2-GGUF-IQ-Imatrix with Ollama:
```
ollama run hf.co/Lewdiculous/SLIDE-v2-GGUF-IQ-Imatrix:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use Lewdiculous/SLIDE-v2-GGUF-IQ-Imatrix with Docker Model Runner:
```
docker model run hf.co/Lewdiculous/SLIDE-v2-GGUF-IQ-Imatrix:Q4_K_M
```

Lemonade

How to use Lewdiculous/SLIDE-v2-GGUF-IQ-Imatrix with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull Lewdiculous/SLIDE-v2-GGUF-IQ-Imatrix:Q4_K_M

Run and chat with the model

lemonade run user.SLIDE-v2-GGUF-IQ-Imatrix-Q4_K_M

List all available models

lemonade list

Atomic Chat

This repository hosts GGUF-IQ-Imatrix quants for NLPark/SLIDE-v2.

From quantization request #23.

Quants:

    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", "IQ2_M",
        "IQ2_S", "IQ3_XS", "IQ4_NL"
    ]

Using the latest of llama.cpp released at the time.

Card image:

Oringinal model card:

Shi-Ci Language Identify & Decode Expositor

7B, Multi-Language...

Prompt Format

Mistral-Instruct

Downloads last month: 186

GGUF

Model size

7B params

Architecture

llama

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Inference Providers NEW

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