Text Classification
Transformers
PyTorch
bert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use Realgon/N_bert_imdb_padding20model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Realgon/N_bert_imdb_padding20model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Realgon/N_bert_imdb_padding20model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Realgon/N_bert_imdb_padding20model") model = AutoModelForSequenceClassification.from_pretrained("Realgon/N_bert_imdb_padding20model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from Realgon/N_bert_imdb_padding20model: direct link, hf CLI and curl.
- Browser
- Download file 573 Bytes
-
https://huggingface.co/Realgon/N_bert_imdb_padding20model/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://Realgon/N_bert_imdb_padding20model/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/Realgon/N_bert_imdb_padding20model/resolve/main/special_tokens_map.json
573 Bytes
| { | |
| "additional_special_tokens": [ | |
| "[PAD_left_1]", | |
| "[PAD_left_2]", | |
| "[PAD_left_3]", | |
| "[PAD_left_4]", | |
| "[PAD_left_5]", | |
| "[PAD_left_6]", | |
| "[PAD_left_7]", | |
| "[PAD_left_8]", | |
| "[PAD_left_9]", | |
| "[PAD_left_10]", | |
| "[PAD_left_11]", | |
| "[PAD_left_12]", | |
| "[PAD_left_13]", | |
| "[PAD_left_14]", | |
| "[PAD_left_15]", | |
| "[PAD_left_16]", | |
| "[PAD_left_17]", | |
| "[PAD_left_18]", | |
| "[PAD_left_19]", | |
| "[PAD_left_20]" | |
| ], | |
| "cls_token": "[CLS]", | |
| "mask_token": "[MASK]", | |
| "pad_token": "[PAD]", | |
| "sep_token": "[SEP]", | |
| "unk_token": "[UNK]" | |
| } | |