Instructions to use thinkingface/test-onnx-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thinkingface/test-onnx-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="thinkingface/test-onnx-2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("thinkingface/test-onnx-2") model = AutoModelForTokenClassification.from_pretrained("thinkingface/test-onnx-2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from thinkingface/test-onnx-2: direct link, hf CLI and curl.
- Browser
- Download file 376 Bytes
-
https://huggingface.co/thinkingface/test-onnx-2/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://thinkingface/test-onnx-2/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/thinkingface/test-onnx-2/resolve/main/tokenizer_config.json
376 Bytes
| { | |
| "add_prefix_space": true, | |
| "bos_token": "<s>", | |
| "clean_up_tokenization_spaces": true, | |
| "cls_token": "<s>", | |
| "do_lower_case": false, | |
| "eos_token": "</s>", | |
| "errors": "replace", | |
| "mask_token": "<mask>", | |
| "model_max_length": 512, | |
| "pad_token": "<pad>", | |
| "sep_token": "</s>", | |
| "tokenizer_class": "RobertaTokenizer", | |
| "trim_offsets": true, | |
| "unk_token": "<unk>" | |
| } | |