Instructions to use owen99630/experience with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use owen99630/experience with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="owen99630/experience")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("owen99630/experience") model = AutoModelForSequenceClassification.from_pretrained("owen99630/experience", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from owen99630/experience: direct link, hf CLI and curl.
- Browser
- Download file 558 Bytes
-
https://huggingface.co/owen99630/experience/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://owen99630/experience/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/owen99630/experience/resolve/main/tokenizer_config.json
558 Bytes
| {"do_lower_case": true, "do_basic_tokenize": true, "never_split": null, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "model_max_length": 512, "special_tokens_map_file": null, "tokenizer_file": "/root/.cache/huggingface/transformers/534479488c54aeaf9c3406f647aa2ec13648c06771ffe269edabebd4c412da1d.7f2721073f19841be16f41b0a70b600ca6b880c8f3df6f3535cbc704371bdfa4", "name_or_path": "bert-base-uncased", "tokenizer_class": "BertTokenizer"} |