Instructions to use DreamFast/Gemma4-e4b-abliterlitics with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use DreamFast/Gemma4-e4b-abliterlitics with Transformers:

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

pipe = pipeline("text-generation", model="DreamFast/Gemma4-e4b-abliterlitics")

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("DreamFast/Gemma4-e4b-abliterlitics", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use DreamFast/Gemma4-e4b-abliterlitics with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "DreamFast/Gemma4-e4b-abliterlitics"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "DreamFast/Gemma4-e4b-abliterlitics",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/DreamFast/Gemma4-e4b-abliterlitics

SGLang

How to use DreamFast/Gemma4-e4b-abliterlitics 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 "DreamFast/Gemma4-e4b-abliterlitics" \
    --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": "DreamFast/Gemma4-e4b-abliterlitics",
		"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 "DreamFast/Gemma4-e4b-abliterlitics" \
        --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": "DreamFast/Gemma4-e4b-abliterlitics",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use DreamFast/Gemma4-e4b-abliterlitics with Docker Model Runner:
```
docker model run hf.co/DreamFast/Gemma4-e4b-abliterlitics
```

Join the Abliterlitics Discord to chat about abliterlitics, models and more.

pinned

by DreamFast - opened 7 days ago

Discussion

DreamFast

Owner 7 days ago

Join the Abliterlitics Discord to chat about abliterlitics, uncensored models and more.

Ask questions, share workflows, or just hang out.

DreamFast pinned discussion 7 days ago

dummy9996

5 days ago

so cringe, your llm could not choose the right license for gemma4 (apache, not gemma tos)
have you licensed your markdown files under the gemma tos 🤣

DreamFast

Owner 5 days ago

so cringe, your llm could not choose the right license for gemma4 (apache, not gemma tos)
have you licensed your markdown files under the gemma tos 🤣

got me there! i did review everything except the tags stuff : ( even that research paper thing. oops. did not know until you pointed it out, thanks.

in the meantime please use these markdown files in accordance to the gemma tos. thank you.

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