Instructions to use thinkingface/test-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thinkingface/test-onnx with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("thinkingface/test-onnx") model = AutoModel.from_pretrained("thinkingface/test-onnx", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from thinkingface/test-onnx: direct link, hf CLI and curl.
- Browser
- Download file 946 Bytes
-
https://huggingface.co/thinkingface/test-onnx/resolve/main/config.json
- Command line
-
hf download hf://thinkingface/test-onnx/config.json
-
curl -L -o config.json https://huggingface.co/thinkingface/test-onnx/resolve/main/config.json
946 Bytes
| { | |
| "_name_or_path": "/tmp/tmp1ctczhyu", | |
| "architectures": [ | |
| "AutoModel" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "classifier_dropout": null, | |
| "eos_token_ids": null, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "O", | |
| "1": "VENDOR", | |
| "2": "DATE", | |
| "3": "HCW", | |
| "4": "HOSPITAL", | |
| "5": "ID", | |
| "6": "PATIENT", | |
| "7": "PHONE" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "DATE": 2, | |
| "HCW": 3, | |
| "HOSPITAL": 4, | |
| "ID": 5, | |
| "O": 0, | |
| "PATIENT": 6, | |
| "PHONE": 7, | |
| "VENDOR": 1 | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "output_past": true, | |
| "pad_token_id": 0, | |
| "position_embedding_type": "absolute", | |
| "transformers_version": "4.30.2", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 30522 | |
| } | |