Instructions to use Camayli/practica8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Camayli/practica8 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Camayli/practica8") model = AutoModelForSeq2SeqLM.from_pretrained("Camayli/practica8") - Notebooks
- Google Colab
- Kaggle
File size: 1,378 Bytes
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"activation_dropout": 0.0,
"activation_function": "swish",
"add_bias_logits": false,
"add_final_layer_norm": false,
"architectures": [
"MarianMTModel"
],
"attention_dropout": 0.0,
"bos_token_id": null,
"classif_dropout": 0.0,
"classifier_dropout": 0.0,
"d_model": 512,
"decoder_attention_heads": 8,
"decoder_ffn_dim": 2048,
"decoder_layerdrop": 0.0,
"decoder_layers": 6,
"decoder_start_token_id": 65000,
"decoder_vocab_size": 65001,
"dropout": 0.1,
"dtype": "float32",
"encoder_attention_heads": 8,
"encoder_ffn_dim": 2048,
"encoder_layerdrop": 0.0,
"encoder_layers": 6,
"eos_token_id": 0,
"extra_pos_embeddings": 65001,
"force_bos_token_to_be_generated": false,
"forced_eos_token_id": 0,
"gradient_checkpointing": false,
"id2label": {
"0": "LABEL_0",
"1": "LABEL_1",
"2": "LABEL_2"
},
"init_std": 0.02,
"is_decoder": false,
"is_encoder_decoder": true,
"label2id": {
"LABEL_0": 0,
"LABEL_1": 1,
"LABEL_2": 2
},
"max_position_embeddings": 512,
"model_type": "marian",
"normalize_before": false,
"normalize_embedding": false,
"pad_token_id": 65000,
"scale_embedding": true,
"share_encoder_decoder_embeddings": true,
"static_position_embeddings": true,
"tie_word_embeddings": true,
"transformers_version": "5.5.0",
"use_cache": false,
"vocab_size": 65001
}
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