Instructions to use bartowski/G2-9B-Blackout-R1-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use bartowski/G2-9B-Blackout-R1-GGUF with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="bartowski/G2-9B-Blackout-R1-GGUF")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("bartowski/G2-9B-Blackout-R1-GGUF", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use bartowski/G2-9B-Blackout-R1-GGUF with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "bartowski/G2-9B-Blackout-R1-GGUF"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "bartowski/G2-9B-Blackout-R1-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/bartowski/G2-9B-Blackout-R1-GGUF

SGLang

How to use bartowski/G2-9B-Blackout-R1-GGUF with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "bartowski/G2-9B-Blackout-R1-GGUF" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "bartowski/G2-9B-Blackout-R1-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "bartowski/G2-9B-Blackout-R1-GGUF" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "bartowski/G2-9B-Blackout-R1-GGUF",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use bartowski/G2-9B-Blackout-R1-GGUF with Docker Model Runner:
```
docker model run hf.co/bartowski/G2-9B-Blackout-R1-GGUF
```

bartowski commited on Sep 13, 2024

Commit

a83ef58

verified ·

1 Parent(s): d9a7084

Upload G2-9B-Blackout-R1-IQ3_M.gguf with huggingface_hub

Browse files

Files changed (2) hide show

.gitattributes +1 -0
G2-9B-Blackout-R1-IQ3_M.gguf +3 -0

.gitattributes CHANGED Viewed

@@ -50,3 +50,4 @@ G2-9B-Blackout-R1-IQ4_XS.gguf filter=lfs diff=lfs merge=lfs -text
 G2-9B-Blackout-R1-Q3_K_XL.gguf filter=lfs diff=lfs merge=lfs -text
 G2-9B-Blackout-R1-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
 G2-9B-Blackout-R1-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text

 G2-9B-Blackout-R1-Q3_K_XL.gguf filter=lfs diff=lfs merge=lfs -text
 G2-9B-Blackout-R1-Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
 G2-9B-Blackout-R1-Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+G2-9B-Blackout-R1-IQ3_M.gguf filter=lfs diff=lfs merge=lfs -text

G2-9B-Blackout-R1-IQ3_M.gguf ADDED Viewed

	@@ -0,0 +1,3 @@

+version https://git-lfs.github.com/spec/v1
+oid sha256:24c642f5f78bb6189da4b44216c878d92993e3fd38116f62e384db08ef076c92
+size 4494615936