Instructions to use steve1989/fingpt-fingpt-SA-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use steve1989/fingpt-fingpt-SA-finetuned with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="steve1989/fingpt-fingpt-SA-finetuned")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("steve1989/fingpt-fingpt-SA-finetuned") model = AutoModelForMultimodalLM.from_pretrained("steve1989/fingpt-fingpt-SA-finetuned") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use steve1989/fingpt-fingpt-SA-finetuned with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "steve1989/fingpt-fingpt-SA-finetuned" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "steve1989/fingpt-fingpt-SA-finetuned", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/steve1989/fingpt-fingpt-SA-finetuned
- SGLang
How to use steve1989/fingpt-fingpt-SA-finetuned 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 "steve1989/fingpt-fingpt-SA-finetuned" \ --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": "steve1989/fingpt-fingpt-SA-finetuned", "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 "steve1989/fingpt-fingpt-SA-finetuned" \ --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": "steve1989/fingpt-fingpt-SA-finetuned", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use steve1989/fingpt-fingpt-SA-finetuned with Docker Model Runner:
docker model run hf.co/steve1989/fingpt-fingpt-SA-finetuned
- Xet hash:
- 4b5008c8ac137ce66bbab8a78c605833e7ea9f01ab0eb39b9d0d1d2225d4ef14
- Size of remote file:
- 4.79 GB
- SHA256:
- 857b42f90f0a02b7d50787439f80deedecac93fa04eef4ae1ebbce43dce752a1
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