Instructions to use jsm33/d4-adaptation with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jsm33/d4-adaptation with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, RobertaForSequenceClassificationWithLayeredSentiment tokenizer = AutoTokenizer.from_pretrained("jsm33/d4-adaptation") model = RobertaForSequenceClassificationWithLayeredSentiment.from_pretrained("jsm33/d4-adaptation", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from jsm33/d4-adaptation: direct link, hf CLI and curl.
- Browser
- Download file 237 Bytes
-
https://huggingface.co/jsm33/d4-adaptation/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://jsm33/d4-adaptation/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/jsm33/d4-adaptation/resolve/main/tokenizer_config.json
237 Bytes
| {"normalization": true, "bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": "<mask>", "model_max_length": 128, "name_or_path": "vinai/bertweet-base"} |