Instructions to use igorktech/hibial-bert-i3-mlm-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use igorktech/hibial-bert-i3-mlm-v0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="igorktech/hibial-bert-i3-mlm-v0.1", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("igorktech/hibial-bert-i3-mlm-v0.1", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "/content/hier-bert-pytorch/data/hibial-model", | |
| "architectures": [ | |
| "HiBiAlBertForMaskedLM" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "auto_map": { | |
| "AutoConfig": "configuration_hibial.HiBiAlBertConfig", | |
| "AutoModel": "modelling_hibial.HiBiAlBertModel", | |
| "AutoModelForMaskedLM": "modelling_hibial.HiBiAlBertForMaskedLM", | |
| "AutoModelForSequenceClassification": "modelling_hibial.HiBiAlBertForSequenceClassification" | |
| }, | |
| "classifier_dropout": null, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 512, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 2048, | |
| "layer_norm_eps": 1e-06, | |
| "max_position_embeddings": 512, | |
| "model_type": "hibial-bert", | |
| "norm_first": true, | |
| "num_attention_heads": 8, | |
| "num_hidden_layers": 6, | |
| "pad_token_id": 0, | |
| "position_embedding_type": "absolute", | |
| "sep_token_id": 3, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.33.2", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 32000 | |
| } | |