Fill-Mask
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
Instructions to use gokulsrinivasagan/tinybert_train_book_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use gokulsrinivasagan/tinybert_train_book_v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="gokulsrinivasagan/tinybert_train_book_v2")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("gokulsrinivasagan/tinybert_train_book_v2") model = AutoModelForMaskedLM.from_pretrained("gokulsrinivasagan/tinybert_train_book_v2") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "distilbert-base-uncased", | |
| "activation": "gelu", | |
| "architectures": [ | |
| "DistilBertForMaskedLM" | |
| ], | |
| "attention_dropout": 0.1, | |
| "dim": 512, | |
| "dropout": 0.1, | |
| "hidden_dim": 3072, | |
| "initializer_range": 0.02, | |
| "max_position_embeddings": 512, | |
| "model_type": "distilbert", | |
| "n_heads": 8, | |
| "n_layers": 4, | |
| "pad_token_id": 0, | |
| "qa_dropout": 0.1, | |
| "seq_classif_dropout": 0.2, | |
| "sinusoidal_pos_embds": false, | |
| "tie_weights_": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.46.1", | |
| "vocab_size": 30522 | |
| } | |