Text Generation
Transformers
Safetensors
English
code
security
qwen3
uncensored
heretic
eve-secure-coder
text-generation-inference
conversational
Instructions to use TitleOS/Eve-4b_LoRA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TitleOS/Eve-4b_LoRA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TitleOS/Eve-4b_LoRA") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TitleOS/Eve-4b_LoRA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use TitleOS/Eve-4b_LoRA with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TitleOS/Eve-4b_LoRA" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TitleOS/Eve-4b_LoRA", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/TitleOS/Eve-4b_LoRA
- SGLang
How to use TitleOS/Eve-4b_LoRA 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 "TitleOS/Eve-4b_LoRA" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TitleOS/Eve-4b_LoRA", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'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 "TitleOS/Eve-4b_LoRA" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TitleOS/Eve-4b_LoRA", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use TitleOS/Eve-4b_LoRA with Docker Model Runner:
docker model run hf.co/TitleOS/Eve-4b_LoRA
Commit History
-
Update README.md
Verified signature0fae950
-
Update README.md
Verified signaturea0cde84
-
Update README.md
Verified signatureb1f69f4
-
Update README.md
Verified signaturea9749c1 -
Model save
Verified signaturea04e62b -
Training in progress, step 932
Verified signature1c14e3e -
Training in progress, step 900
Verified signature0aab862 -
Training in progress, step 850
Verified signature6d4203e -
Training in progress, step 800
Verified signatureac8ffc8 -
Training in progress, step 750
Verified signature046bd19 -
Training in progress, step 700
Verified signature5188013 -
Training in progress, step 650
Verified signature508c293 -
Training in progress, step 600
Verified signature081a16b -
Training in progress, step 550
Verified signature735d27f -
Training in progress, step 500
Verified signatureae2ba58 -
Training in progress, step 450
Verified signature393e1a1 -
Training in progress, step 400
Verified signature428e385 -
Training in progress, step 350
Verified signature05eb525 -
Training in progress, step 300
Verified signature76da651 -
Training in progress, step 250
Verified signature220e0a2 -
Training in progress, step 200
Verified signature5db6cf7 -
Training in progress, step 150
Verified signature3c28d69 -
Training in progress, step 100
Verified signaturefad2f4e -
Create README.md
Verified signatureed03b16 -
Training in progress, step 50
Verified signature01e515c -
initial commit
Verified signaturec6d2a22