Text Classification
Transformers
Safetensors
Portuguese
deberta
fake-news
sequence-classification
portuguese
Eval Results (legacy)
Instructions to use HenriqueLz/albertina-100m-portuguese-ptbr-fakerecogna2-extrativa-elections with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HenriqueLz/albertina-100m-portuguese-ptbr-fakerecogna2-extrativa-elections with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HenriqueLz/albertina-100m-portuguese-ptbr-fakerecogna2-extrativa-elections")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HenriqueLz/albertina-100m-portuguese-ptbr-fakerecogna2-extrativa-elections") model = AutoModelForSequenceClassification.from_pretrained("HenriqueLz/albertina-100m-portuguese-ptbr-fakerecogna2-extrativa-elections", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from HenriqueLz/albertina-100m-portuguese-ptbr-fakerecogna2-extrativa-elections: direct link, hf CLI and curl.
- Browser
- Download file 920 Bytes
-
https://huggingface.co/HenriqueLz/albertina-100m-portuguese-ptbr-fakerecogna2-extrativa-elections/resolve/main/config.json
- Command line
-
hf download hf://HenriqueLz/albertina-100m-portuguese-ptbr-fakerecogna2-extrativa-elections/config.json
-
curl -L -o config.json https://huggingface.co/HenriqueLz/albertina-100m-portuguese-ptbr-fakerecogna2-extrativa-elections/resolve/main/config.json
920 Bytes
| { | |
| "architectures": [ | |
| "DebertaForSequenceClassification" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "id2label": { | |
| "0": "NEGATIVE", | |
| "1": "POSITIVE" | |
| }, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "label2id": { | |
| "NEGATIVE": 0, | |
| "POSITIVE": 1 | |
| }, | |
| "layer_norm_eps": 1e-07, | |
| "legacy": true, | |
| "max_position_embeddings": 512, | |
| "max_relative_positions": -1, | |
| "model_type": "deberta", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "pooler_dropout": 0, | |
| "pooler_hidden_act": "gelu", | |
| "pooler_hidden_size": 768, | |
| "pos_att_type": [ | |
| "c2p", | |
| "p2c" | |
| ], | |
| "position_biased_input": false, | |
| "relative_attention": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.51.3", | |
| "type_vocab_size": 0, | |
| "vocab_size": 50265 | |
| } | |