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
| { | |
| "_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 | |
| } | |