Instructions to use facebook/bart-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use facebook/bart-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="facebook/bart-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("facebook/bart-base") model = AutoModel.from_pretrained("facebook/bart-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 1,716 Bytes
e658f90 b0c3779 b2ec1a3 e658f90 c5eee23 e658f90 b2ec1a3 e658f90 b2ec1a3 c5eee23 e658f90 d7db7a7 e658f90 2557745 e658f90 b2ec1a3 d7db7a7 e658f90 c5eee23 d0af988 c5eee23 e658f90 c5eee23 e658f90 c5eee23 e658f90 b2ec1a3 c5eee23 b2ec1a3 b0c3779 c5eee23 a0f3da1 e658f90 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 | {
"_name_or_path": "bart-base",
"activation_dropout": 0.1,
"activation_function": "gelu",
"add_bias_logits": false,
"add_final_layer_norm": false,
"architectures": [
"BartModel"
],
"attention_dropout": 0.1,
"bos_token_id": 0,
"classif_dropout": 0.1,
"classifier_dropout": 0.0,
"d_model": 768,
"decoder_attention_heads": 12,
"decoder_ffn_dim": 3072,
"decoder_layerdrop": 0.0,
"decoder_layers": 6,
"decoder_start_token_id": 2,
"dropout": 0.1,
"early_stopping": true,
"encoder_attention_heads": 12,
"encoder_ffn_dim": 3072,
"encoder_layerdrop": 0.0,
"encoder_layers": 6,
"eos_token_id": 2,
"forced_eos_token_id": 2,
"forced_bos_token_id": 0,
"gradient_checkpointing": false,
"id2label": {
"0": "LABEL_0",
"1": "LABEL_1",
"2": "LABEL_2"
},
"init_std": 0.02,
"is_encoder_decoder": true,
"label2id": {
"LABEL_0": 0,
"LABEL_1": 1,
"LABEL_2": 2
},
"max_position_embeddings": 1024,
"model_type": "bart",
"no_repeat_ngram_size": 3,
"normalize_before": false,
"normalize_embedding": true,
"num_beams": 4,
"num_hidden_layers": 6,
"pad_token_id": 1,
"scale_embedding": false,
"task_specific_params": {
"summarization": {
"length_penalty": 1.0,
"max_length": 128,
"min_length": 12,
"num_beams": 4
},
"summarization_cnn": {
"length_penalty": 2.0,
"max_length": 142,
"min_length": 56,
"num_beams": 4
},
"summarization_xsum": {
"length_penalty": 1.0,
"max_length": 62,
"min_length": 11,
"num_beams": 6
}
},
"torch_dtype": "float32",
"transformers_version": "4.12.0.dev0",
"use_cache": true,
"vocab_size": 50265
}
|