Instructions to use basaadi/tifinagh-ocr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use basaadi/tifinagh-ocr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="basaadi/tifinagh-ocr")# Load model directly from transformers import AutoTokenizer, AutoModelForImageTextToText tokenizer = AutoTokenizer.from_pretrained("basaadi/tifinagh-ocr") model = AutoModelForImageTextToText.from_pretrained("basaadi/tifinagh-ocr") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use basaadi/tifinagh-ocr with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "basaadi/tifinagh-ocr" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "basaadi/tifinagh-ocr", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/basaadi/tifinagh-ocr
- SGLang
How to use basaadi/tifinagh-ocr 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 "basaadi/tifinagh-ocr" \ --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": "basaadi/tifinagh-ocr", "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 "basaadi/tifinagh-ocr" \ --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": "basaadi/tifinagh-ocr", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use basaadi/tifinagh-ocr with Docker Model Runner:
docker model run hf.co/basaadi/tifinagh-ocr
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"_from_model_config": false,
"assistant_confidence_threshold": 0.4,
"assistant_lookbehind": 10,
"bos_token_id": 0,
"decoder_start_token_id": 2,
"diversity_penalty": 0.0,
"do_sample": false,
"early_stopping": false,
"encoder_no_repeat_ngram_size": 0,
"encoder_repetition_penalty": 1.0,
"eos_token_id": 2,
"epsilon_cutoff": 0.0,
"eta_cutoff": 0.0,
"length_penalty": 1.0,
"max_length": 20,
"min_length": 0,
"no_repeat_ngram_size": 0,
"num_assistant_tokens": 20,
"num_assistant_tokens_schedule": "constant",
"num_beam_groups": 1,
"num_beams": 1,
"num_return_sequences": 1,
"output_attentions": false,
"output_hidden_states": false,
"output_scores": false,
"pad_token_id": 1,
"remove_invalid_values": false,
"repetition_penalty": 1.0,
"return_dict_in_generate": false,
"target_lookbehind": 10,
"temperature": 1.0,
"top_k": 50,
"top_p": 1.0,
"transformers_version": "5.5.4",
"typical_p": 1.0,
"use_cache": true
}
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