Instructions to use hf-internal-testing/tiny-random-ErnieMForTokenClassification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hf-internal-testing/tiny-random-ErnieMForTokenClassification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="hf-internal-testing/tiny-random-ErnieMForTokenClassification")# Load model directly from transformers import AutoModelForTokenClassification model = AutoModelForTokenClassification.from_pretrained("hf-internal-testing/tiny-random-ErnieMForTokenClassification", dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "cls_token": "[CLS]", | |
| "do_lower_case": false, | |
| "encoding": "utf8", | |
| "mask_token": "[MASK]", | |
| "model_max_length": 512, | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "sp_model_kwargs": {}, | |
| "special_tokens_map_file": "/home/runner/.cache/huggingface/hub/models--susnato--ernie-m-base_pytorch/snapshots/dc3909120bc2c81f9e527b758df2b3ba79b63720/special_tokens_map.json", | |
| "tokenizer_class": "ErnieMTokenizer", | |
| "unk_token": "[UNK]" | |
| } | |