Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use GioReg/bertNEGsentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GioReg/bertNEGsentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="GioReg/bertNEGsentiment")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("GioReg/bertNEGsentiment") model = AutoModelForSequenceClassification.from_pretrained("GioReg/bertNEGsentiment", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from GioReg/bertNEGsentiment: direct link, hf CLI and curl.
- Browser
- Download file 389 Bytes
-
https://huggingface.co/GioReg/bertNEGsentiment/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://GioReg/bertNEGsentiment/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/GioReg/bertNEGsentiment/resolve/main/tokenizer_config.json
389 Bytes
| {"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "special_tokens_map_file": null, "name_or_path": "m-polignano-uniba/bert_uncased_L-12_H-768_A-12_italian_alb3rt0", "do_basic_tokenize": true, "never_split": null, "tokenizer_class": "BertTokenizer"} |