Instructions to use SebastianBodza/DElefant with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SebastianBodza/DElefant with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="SebastianBodza/DElefant")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("SebastianBodza/DElefant") model = AutoModelForCausalLM.from_pretrained("SebastianBodza/DElefant", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use SebastianBodza/DElefant with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SebastianBodza/DElefant" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SebastianBodza/DElefant", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SebastianBodza/DElefant
- SGLang
How to use SebastianBodza/DElefant 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 "SebastianBodza/DElefant" \ --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": "SebastianBodza/DElefant", "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 "SebastianBodza/DElefant" \ --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": "SebastianBodza/DElefant", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use SebastianBodza/DElefant with Docker Model Runner:
docker model run hf.co/SebastianBodza/DElefant
Commit History
-
Model commit
Sebastian Bodzad4155bf -
Update README.md
Bugfix linkse9f5b1b -
Update README.md
4d593c9 -
Upload train_loss_DElefant.svg
Updated with axis labels644175c -
Upload train_loss_DElefant.svg
ec15d14 -
Upload badge_gerlefant.png
Removed backgroundd96970a -
Upload badge_gerlefant.png
a417bcc -
initial commit
Sebastian Bodza24b71df