Instructions to use cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-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 cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-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 cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF:Q2_K
# Run inference directly in the terminal:
llama cli -hf cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF:Q2_K

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF:Q2_K
# Run inference directly in the terminal:
llama cli -hf cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF:Q2_K

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 cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF:Q2_K
# Run inference directly in the terminal:
./llama-cli -hf cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF:Q2_K

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 cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF:Q2_K
# Run inference directly in the terminal:
./build/bin/llama-cli -hf cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF:Q2_K

Use Docker

docker model run hf.co/cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF:Q2_K

LM Studio
Jan

vLLM

How to use cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF:Q2_K

Ollama
How to use cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF with Ollama:
```
ollama run hf.co/cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF:Q2_K
```
Unsloth Desktop
Docker Model Runner
How to use cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF with Docker Model Runner:
```
docker model run hf.co/cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF:Q2_K
```

Lemonade

How to use cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull cyberneurova/CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF:Q2_K

Run and chat with the model

lemonade run user.CyberNeurova-DeepSeek-V4-Flash-abliterated-GGUF-Q2_K

List all available models

lemonade list

Atomic Chat

BF16 or FP8/FP4 mixed .safetensors version?

by aabbccddwasd - opened May 10

Discussion

aabbccddwasd

May 10

for vllm inference

aabbccddwasd changed discussion title from BF16 or FP8/FP4 mixed version? to BF16 or FP8/FP4 mixed .safetensors version? May 10

alonsoko

May 11

Hey, joining-in on the conversation.
If you could make an AWQ/GPTQ version so we could do VLLM inference it would be great.

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