Instructions to use vumichien/tiny-albert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vumichien/tiny-albert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="vumichien/tiny-albert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("vumichien/tiny-albert") model = AutoModelForTokenClassification.from_pretrained("vumichien/tiny-albert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from vumichien/tiny-albert: direct link, hf CLI and curl.
- Browser
- Download file 671 Bytes
-
https://huggingface.co/vumichien/tiny-albert/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://vumichien/tiny-albert/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/vumichien/tiny-albert/resolve/main/tokenizer_config.json
671 Bytes
| {"do_lower_case": true, "remove_space": true, "keep_accents": false, "bos_token": "[CLS]", "eos_token": "[SEP]", "unk_token": "<unk>", "sep_token": "[SEP]", "pad_token": "<pad>", "cls_token": "[CLS]", "mask_token": {"content": "[MASK]", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "sp_model_kwargs": {}, "model_max_length": 256, "special_tokens_map_file": "/root/.cache/huggingface/transformers/e0f085d5ba6003dd56d84de7485216c332f557b7c0eb99b00ebeddbf6e91c106.15ed5b79b197b4fcc5f3f80b2ee89a5a3ad708dbd076575cd22cffd9e1a56284", "name_or_path": "hf-internal-testing/tiny-albert", "tokenizer_class": "AlbertTokenizer"} |