Image-Text-to-Text
Transformers
Safetensors
Standard Moroccan Tamazight
Central Atlas Tamazight
Tachelhit
vision-encoder-decoder
Instructions to use Tamazight/TrOCR-Tifinagh-Small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Tamazight/TrOCR-Tifinagh-Small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="Tamazight/TrOCR-Tifinagh-Small")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("Tamazight/TrOCR-Tifinagh-Small") model = AutoModelForImageTextToText.from_pretrained("Tamazight/TrOCR-Tifinagh-Small") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Tamazight/TrOCR-Tifinagh-Small with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Tamazight/TrOCR-Tifinagh-Small" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Tamazight/TrOCR-Tifinagh-Small", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Tamazight/TrOCR-Tifinagh-Small
- SGLang
How to use Tamazight/TrOCR-Tifinagh-Small 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 "Tamazight/TrOCR-Tifinagh-Small" \ --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": "Tamazight/TrOCR-Tifinagh-Small", "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 "Tamazight/TrOCR-Tifinagh-Small" \ --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": "Tamazight/TrOCR-Tifinagh-Small", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Tamazight/TrOCR-Tifinagh-Small with Docker Model Runner:
docker model run hf.co/Tamazight/TrOCR-Tifinagh-Small
| { | |
| "add_prefix_space": false, | |
| "backend": "tokenizers", | |
| "bos_token": "<s>", | |
| "cls_token": "<s>", | |
| "eos_token": "</s>", | |
| "errors": "replace", | |
| "is_local": true, | |
| "mask_token": "<mask>", | |
| "model_max_length": 1000000000000000019884624838656, | |
| "pad_token": "<pad>", | |
| "processor_class": "TrOCRProcessor", | |
| "sep_token": "</s>", | |
| "sp_model_kwargs": {}, | |
| "tokenizer_class": "RobertaTokenizer", | |
| "trim_offsets": true, | |
| "unk_token": "<unk>" | |
| } | |