Text Classification
Transformers
PyTorch
TensorBoard
bert
Generated from Trainer
text-embeddings-inference
Instructions to use caush/Clickbait1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use caush/Clickbait1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="caush/Clickbait1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("caush/Clickbait1") model = AutoModelForSequenceClassification.from_pretrained("caush/Clickbait1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 583 Bytes
2cab340 | 1 | {"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "special_tokens_map_file": "/root/.cache/huggingface/transformers/8ed73a1ab9ef4e90a9451497bf96cfc38d34354352838a143f2dda1c81aed5ca.0dc5b1041f62041ebbd23b1297f2f573769d5c97d8b7c28180ec86b8f6185aa8", "name_or_path": "microsoft/Multilingual-MiniLM-L12-H384", "sp_model_kwargs": {}, "tokenizer_class": "XLMRobertaTokenizer"} |