Instructions to use lakshaya17/phi2-srl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use lakshaya17/phi2-srl with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("microsoft/phi-2") model = PeftModel.from_pretrained(base_model, "lakshaya17/phi2-srl") - Transformers
How to use lakshaya17/phi2-srl with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="lakshaya17/phi2-srl")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("lakshaya17/phi2-srl", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use lakshaya17/phi2-srl with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "lakshaya17/phi2-srl" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lakshaya17/phi2-srl", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/lakshaya17/phi2-srl
- SGLang
How to use lakshaya17/phi2-srl 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 "lakshaya17/phi2-srl" \ --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": "lakshaya17/phi2-srl", "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 "lakshaya17/phi2-srl" \ --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": "lakshaya17/phi2-srl", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use lakshaya17/phi2-srl with Docker Model Runner:
docker model run hf.co/lakshaya17/phi2-srl
Download added_tokens.json from lakshaya17/phi2-srl: direct link, hf CLI and curl.
- Browser
- Download file 1.1 kB
-
https://huggingface.co/lakshaya17/phi2-srl/resolve/main/added_tokens.json
- Command line
-
hf download hf://lakshaya17/phi2-srl/added_tokens.json
-
curl -L -o added_tokens.json https://huggingface.co/lakshaya17/phi2-srl/resolve/main/added_tokens.json
1.1 kB
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