Instructions to use Deborah/custom-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Deborah/custom-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="Deborah/custom-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("Deborah/custom-model") model = AutoModelForTokenClassification.from_pretrained("Deborah/custom-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from Deborah/custom-model: direct link, hf CLI and curl.
- Browser
- Download file 1.49 kB
-
https://huggingface.co/Deborah/custom-model/resolve/refs%2Fpr%2F1/config.json
- Command line
-
hf download hf://Deborah/custom-model@refs/pr/1/config.json
-
curl -L -o config.json https://huggingface.co/Deborah/custom-model/resolve/refs%2Fpr%2F1/config.json
1.49 kB
| { | |
| "_name_or_path": "neuralmind/bert-base-portuguese-cased", | |
| "architectures": [ | |
| "BertForTokenClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "classifier_dropout": null, | |
| "directionality": "bidi", | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "ADJ", | |
| "1": "ADP", | |
| "10": "PRON", | |
| "11": "PROPN", | |
| "12": "PUNCT", | |
| "13": "SCONJ", | |
| "14": "SYM", | |
| "15": "VERB", | |
| "16": "X", | |
| "2": "ADV", | |
| "3": "AUX", | |
| "4": "CCONJ", | |
| "5": "DET", | |
| "6": "INTJ", | |
| "7": "NOUN", | |
| "8": "NUM", | |
| "9": "PART" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "ADJ": "0", | |
| "ADP": "1", | |
| "ADV": "2", | |
| "AUX": "3", | |
| "CCONJ": "4", | |
| "DET": "5", | |
| "INTJ": "6", | |
| "NOUN": "7", | |
| "NUM": "8", | |
| "PART": "9", | |
| "PRON": "10", | |
| "PROPN": "11", | |
| "PUNCT": "12", | |
| "SCONJ": "13", | |
| "SYM": "14", | |
| "VERB": "15", | |
| "X": "16" | |
| }, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "output_past": true, | |
| "pad_token_id": 0, | |
| "pooler_fc_size": 768, | |
| "pooler_num_attention_heads": 12, | |
| "pooler_num_fc_layers": 3, | |
| "pooler_size_per_head": 128, | |
| "pooler_type": "first_token_transform", | |
| "position_embedding_type": "absolute", | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.19.4", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 29794 | |
| } | |