Instructions to use rushai-dev/THAI-TrOCR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rushai-dev/THAI-TrOCR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="rushai-dev/THAI-TrOCR")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("rushai-dev/THAI-TrOCR") model = AutoModelForImageTextToText.from_pretrained("rushai-dev/THAI-TrOCR") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use rushai-dev/THAI-TrOCR with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "rushai-dev/THAI-TrOCR" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rushai-dev/THAI-TrOCR", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/rushai-dev/THAI-TrOCR
- SGLang
How to use rushai-dev/THAI-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 "rushai-dev/THAI-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": "rushai-dev/THAI-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 "rushai-dev/THAI-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": "rushai-dev/THAI-TrOCR", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use rushai-dev/THAI-TrOCR with Docker Model Runner:
docker model run hf.co/rushai-dev/THAI-TrOCR
- Xet hash:
- 1ab9ce98cc7035f5e52afc08c0dfa506354dde140bb6650ef634cf82f1522b11
- Size of remote file:
- 1.57 GB
- SHA256:
- 1c5039d08dc242e864e9ec8082307fdc6459350c913eab41a77ecf1b142c3c57
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