Text Generation
Transformers
Safetensors
English
phi-3
lora
payments
finance
information-extraction
structured-data-extraction
text-to-data
finetuned
conversational
Instructions to use aamanlamba/phi3-payments-reverse-finetune with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aamanlamba/phi3-payments-reverse-finetune with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="aamanlamba/phi3-payments-reverse-finetune") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("aamanlamba/phi3-payments-reverse-finetune", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use aamanlamba/phi3-payments-reverse-finetune with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "aamanlamba/phi3-payments-reverse-finetune" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "aamanlamba/phi3-payments-reverse-finetune", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/aamanlamba/phi3-payments-reverse-finetune
- SGLang
How to use aamanlamba/phi3-payments-reverse-finetune 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 "aamanlamba/phi3-payments-reverse-finetune" \ --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": "aamanlamba/phi3-payments-reverse-finetune", "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 "aamanlamba/phi3-payments-reverse-finetune" \ --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": "aamanlamba/phi3-payments-reverse-finetune", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use aamanlamba/phi3-payments-reverse-finetune with Docker Model Runner:
docker model run hf.co/aamanlamba/phi3-payments-reverse-finetune
- Xet hash:
- c3afe9bb6934d89b7863cebb4f4798ff6a9b7b70a76770d5c372796760c52bf6
- Size of remote file:
- 5.37 kB
- SHA256:
- 24f90672e9aadeb1cee3d6335a1992fa5225b90bc948cee5a8175a6e01426a28
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