Instructions to use RemySkye/rwkv7-g1g-7.2b-i1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use RemySkye/rwkv7-g1g-7.2b-i1-GGUF with RWKV:

# No code snippets available yet for this library.

# To use this model, check the repository files and the library's documentation.

# Want to help? PRs adding snippets are welcome at:
# https://github.com/huggingface/huggingface.js

Notebooks
Google Colab
Kaggle
Local Apps Settings

llama.cpp

How to use RemySkye/rwkv7-g1g-7.2b-i1-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 RemySkye/rwkv7-g1g-7.2b-i1-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf RemySkye/rwkv7-g1g-7.2b-i1-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 RemySkye/rwkv7-g1g-7.2b-i1-GGUF:Q4_K_M
# Run inference directly in the terminal:
llama cli -hf RemySkye/rwkv7-g1g-7.2b-i1-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 RemySkye/rwkv7-g1g-7.2b-i1-GGUF:Q4_K_M
# Run inference directly in the terminal:
./llama-cli -hf RemySkye/rwkv7-g1g-7.2b-i1-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 RemySkye/rwkv7-g1g-7.2b-i1-GGUF:Q4_K_M
# Run inference directly in the terminal:
./build/bin/llama-cli -hf RemySkye/rwkv7-g1g-7.2b-i1-GGUF:Q4_K_M

Use Docker

docker model run hf.co/RemySkye/rwkv7-g1g-7.2b-i1-GGUF:Q4_K_M

LM Studio
Jan

vLLM

How to use RemySkye/rwkv7-g1g-7.2b-i1-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "RemySkye/rwkv7-g1g-7.2b-i1-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "RemySkye/rwkv7-g1g-7.2b-i1-GGUF",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/RemySkye/rwkv7-g1g-7.2b-i1-GGUF:Q4_K_M

Ollama
How to use RemySkye/rwkv7-g1g-7.2b-i1-GGUF with Ollama:
```
ollama run hf.co/RemySkye/rwkv7-g1g-7.2b-i1-GGUF:Q4_K_M
```
Unsloth Desktop
Docker Model Runner
How to use RemySkye/rwkv7-g1g-7.2b-i1-GGUF with Docker Model Runner:
```
docker model run hf.co/RemySkye/rwkv7-g1g-7.2b-i1-GGUF:Q4_K_M
```

Lemonade

How to use RemySkye/rwkv7-g1g-7.2b-i1-GGUF with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull RemySkye/rwkv7-g1g-7.2b-i1-GGUF:Q4_K_M

Run and chat with the model

lemonade run user.rwkv7-g1g-7.2b-i1-GGUF-Q4_K_M

List all available models

lemonade list

Atomic Chat

RWKV7-G1G 7.2B - GGUF Quantizations

GGUF conversions of BlinkDL/rwkv7-g1g-7.2b (Apache 2.0)
for use with llama.cpp, LM Studio, and other GGUF-compatible runtimes.

All quants converted from BF16 base for maximum lossless quality. Used imatrix generated with https://gist.github.com/bartowski1182/82ae9b520227f57d79ba04add13d0d0d

See UncheatableEval for benchmarks.

Downloads last month: 470

GGUF

Model size

7B params

Architecture

rwkv7

Hardware compatibility

2-bit

3-bit

4-bit

5-bit

6-bit

View +1 variant

Model tree for RemySkye/rwkv7-g1g-7.2b-i1-GGUF

Base model

BlinkDL/rwkv7-g1

Quantized

(36)

this model

Collection including RemySkye/rwkv7-g1g-7.2b-i1-GGUF

RWKV7 G1G GGUF

Collection

4 items • Updated Aug 17 • 1