Instructions to use sejalv/Fine_Tuned_LP_TROCR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sejalv/Fine_Tuned_LP_TROCR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="sejalv/Fine_Tuned_LP_TROCR")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("sejalv/Fine_Tuned_LP_TROCR") model = AutoModelForImageTextToText.from_pretrained("sejalv/Fine_Tuned_LP_TROCR") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use sejalv/Fine_Tuned_LP_TROCR with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "sejalv/Fine_Tuned_LP_TROCR" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "sejalv/Fine_Tuned_LP_TROCR", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/sejalv/Fine_Tuned_LP_TROCR
- SGLang
How to use sejalv/Fine_Tuned_LP_TROCR 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 "sejalv/Fine_Tuned_LP_TROCR" \ --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": "sejalv/Fine_Tuned_LP_TROCR", "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 "sejalv/Fine_Tuned_LP_TROCR" \ --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": "sejalv/Fine_Tuned_LP_TROCR", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use sejalv/Fine_Tuned_LP_TROCR with Docker Model Runner:
docker model run hf.co/sejalv/Fine_Tuned_LP_TROCR
| { | |
| "bos_token_id": 0, | |
| "decoder_start_token_id": 0, | |
| "early_stopping": true, | |
| "eos_token_id": 2, | |
| "length_penalty": 2.0, | |
| "max_length": 64, | |
| "no_repeat_ngram_size": 3, | |
| "num_beams": 4, | |
| "pad_token_id": 1, | |
| "transformers_version": "4.42.4", | |
| "use_cache": false | |
| } | |