Instructions to use hansgun/model_test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hansgun/model_test2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="hansgun/model_test2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("hansgun/model_test2") model = AutoModel.from_pretrained("hansgun/model_test2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from hansgun/model_test2: direct link, hf CLI and curl.
- Browser
- Download file 347 Bytes
-
https://huggingface.co/hansgun/model_test2/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://hansgun/model_test2/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/hansgun/model_test2/resolve/main/tokenizer_config.json
347 Bytes
| {"do_lower_case": false, "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, "max_len": 512, "special_tokens_map_file": null, "tokenizer_file": null, "name_or_path": "monologg/kobert"} |