Instructions to use whu9/multi_doc_sum_slide_token with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use whu9/multi_doc_sum_slide_token with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, NetSum tokenizer = AutoTokenizer.from_pretrained("whu9/multi_doc_sum_slide_token") model = NetSum.from_pretrained("whu9/multi_doc_sum_slide_token", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 615 Bytes
758c37d | 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 | {
"architectures": [
"NetSum"
],
"d_ff": 2048,
"d_kv": 64,
"d_model": 512,
"dropout": 0.2,
"dropout_rate": 0.1,
"eos_token_id": 1,
"feed_forward_proj": "relu",
"hidden_size1": 128,
"hidden_size2": 512,
"initializer_factor": 1.0,
"is_encoder_decoder": true,
"layer_norm_epsilon": 1e-06,
"model_type": "t5",
"num_decoder_layers": 6,
"num_heads": 8,
"num_layer": 1,
"num_layers": 6,
"output_size": 3072,
"pad_token_id": 0,
"relative_attention_num_buckets": 32,
"torch_dtype": "float32",
"transformers_version": "4.17.0",
"use_cache": true,
"vocab_size": 32128
}
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