Instructions to use safffrron/25M2111-Week01-Track2-40-Submission01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use safffrron/25M2111-Week01-Track2-40-Submission01 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="safffrron/25M2111-Week01-Track2-40-Submission01")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("safffrron/25M2111-Week01-Track2-40-Submission01", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use safffrron/25M2111-Week01-Track2-40-Submission01 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "safffrron/25M2111-Week01-Track2-40-Submission01" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "safffrron/25M2111-Week01-Track2-40-Submission01", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/safffrron/25M2111-Week01-Track2-40-Submission01
- SGLang
How to use safffrron/25M2111-Week01-Track2-40-Submission01 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 "safffrron/25M2111-Week01-Track2-40-Submission01" \ --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": "safffrron/25M2111-Week01-Track2-40-Submission01", "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 "safffrron/25M2111-Week01-Track2-40-Submission01" \ --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": "safffrron/25M2111-Week01-Track2-40-Submission01", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use safffrron/25M2111-Week01-Track2-40-Submission01 with Docker Model Runner:
docker model run hf.co/safffrron/25M2111-Week01-Track2-40-Submission01
Ctrl+K
Delete files src/eaimath.egg-info/PKG-INFO src/eaimath.egg-info/SOURCES.txt src/eaimath.egg-info/dependency_links.txt src/eaimath.egg-info/requires.txt src/eaimath.egg-info/top_level.txt src/eaimath/__pycache__/__init__.cpython-311.pyc src/eaimath/__pycache__/adaptive_artifact.cpython-311.pyc src/eaimath/__pycache__/answers.cpython-311.pyc src/eaimath/__pycache__/artifact.cpython-311.pyc src/eaimath/__pycache__/buckets.cpython-311.pyc src/eaimath/__pycache__/data.cpython-311.pyc src/eaimath/__pycache__/delta_sharing.cpython-311.pyc src/eaimath/__pycache__/embedding_predictor.cpython-311.pyc src/eaimath/__pycache__/evaluate.cpython-311.pyc src/eaimath/__pycache__/extreme_quant.cpython-311.pyc src/eaimath/__pycache__/gauge.cpython-311.pyc src/eaimath/__pycache__/generate.cpython-311.pyc src/eaimath/__pycache__/ledger.cpython-311.pyc src/eaimath/__pycache__/model.cpython-311.pyc src/eaimath/__pycache__/pack.cpython-311.pyc src/eaimath/__pycache__/peft_compat.cpython-311.pyc src/eaimath/__pycache__/quantize.cpython-311.pyc src/eaimath/__pycache__/rate_distortion.cpython-311.pyc src/eaimath/__pycache__/sharing.cpython-311.pyc src/eaimath/__pycache__/vllm_backend.cpython-311.pyc src/eaimath/__pycache__/vocab.cpython-311.pyc with huggingface_hub
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