Instructions to use ubiodee/Cardano_plutus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ubiodee/Cardano_plutus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ubiodee/Cardano_plutus")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ubiodee/Cardano_plutus") model = AutoModelForCausalLM.from_pretrained("ubiodee/Cardano_plutus", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ubiodee/Cardano_plutus with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ubiodee/Cardano_plutus" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ubiodee/Cardano_plutus", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ubiodee/Cardano_plutus
- SGLang
How to use ubiodee/Cardano_plutus 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 "ubiodee/Cardano_plutus" \ --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": "ubiodee/Cardano_plutus", "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 "ubiodee/Cardano_plutus" \ --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": "ubiodee/Cardano_plutus", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ubiodee/Cardano_plutus with Docker Model Runner:
docker model run hf.co/ubiodee/Cardano_plutus
Commit History
-
Upload tokenizer
Verified signature001c1ec -
Training in progress, step 79
Verified signatureb6b37a5 -
Delete .gitattributes
Verified signaturefe0639c -
Upload tokenizer
Verified signatured92fb2e -
Training in progress, step 316
Verified signature4b1b3d8 -
Delete .gitattributes
Verified signature7193571
-
Upload tokenizer
Verified signature9fa1bf2 -
Training in progress, step 316
Verified signature49cbda8 -
Delete .gitattributes
Verified signatureadd7bc8
-
initial commit
Verified signaturec7f05ce