Text Generation
Transformers
English
uncensored
abliterated
qwen2.5
apostate
huihui
heretic
harmbench
forensics
Instructions to use DreamFast/Qwen-2.5-7b-abliterlitics with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DreamFast/Qwen-2.5-7b-abliterlitics with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="DreamFast/Qwen-2.5-7b-abliterlitics")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("DreamFast/Qwen-2.5-7b-abliterlitics", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use DreamFast/Qwen-2.5-7b-abliterlitics with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "DreamFast/Qwen-2.5-7b-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/Qwen-2.5-7b-abliterlitics", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/DreamFast/Qwen-2.5-7b-abliterlitics
- SGLang
How to use DreamFast/Qwen-2.5-7b-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/Qwen-2.5-7b-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/Qwen-2.5-7b-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/Qwen-2.5-7b-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/Qwen-2.5-7b-abliterlitics", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use DreamFast/Qwen-2.5-7b-abliterlitics with Docker Model Runner:
docker model run hf.co/DreamFast/Qwen-2.5-7b-abliterlitics
| { | |
| "name": "qwen25-7b", | |
| "base": "../../models/Qwen2.5-7B-Instruct", | |
| "variants": { | |
| "apostate": { | |
| "path": "../../models/qwen-2.5-7b-apostate", | |
| "display_name": "Apostate" | |
| }, | |
| "huihui": { | |
| "path": "../../models/Qwen2.5-7B-Instruct-abliterated-v2", | |
| "display_name": "Huihui" | |
| }, | |
| "heretic": { | |
| "path": "../../models/Qwen2.5-7B-Instruct-heretic-1.3.0", | |
| "display_name": "Heretic" | |
| } | |
| }, | |
| "settings": { | |
| "inference_backend": "vllm", | |
| "tokenizer_dir": "../../models/Qwen2.5-7B-Instruct", | |
| "lm_eval_max_model_len": 8192, | |
| "lm_eval_max_gen_toks": 2048, | |
| "harmbench_max_tokens": 4096 | |
| } | |
| } | |