Question Answering
Transformers
TensorBoard
Safetensors
English
longformer
Generated from Trainer
qsi
quote_speaker_identification
Eval Results (legacy)
Instructions to use Kkordik/test_longformer_4096_qsi with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kkordik/test_longformer_4096_qsi with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="Kkordik/test_longformer_4096_qsi")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("Kkordik/test_longformer_4096_qsi") model = AutoModelForQuestionAnswering.from_pretrained("Kkordik/test_longformer_4096_qsi", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 914 Bytes
4389ada | 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 | {
"_name_or_path": "mrm8488/longformer-base-4096-finetuned-squadv2",
"architectures": [
"LongformerForQuestionAnswering"
],
"attention_mode": "longformer",
"attention_probs_dropout_prob": 0.1,
"attention_window": [
512,
512,
512,
512,
512,
512,
512,
512,
512,
512,
512,
512
],
"bos_token_id": 0,
"eos_token_id": 2,
"gradient_checkpointing": false,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"ignore_attention_mask": false,
"initializer_range": 0.02,
"intermediate_size": 3072,
"layer_norm_eps": 1e-05,
"max_position_embeddings": 4098,
"model_type": "longformer",
"num_attention_heads": 12,
"num_hidden_layers": 12,
"onnx_export": false,
"pad_token_id": 1,
"sep_token_id": 2,
"torch_dtype": "float32",
"transformers_version": "4.35.2",
"type_vocab_size": 1,
"vocab_size": 50265
}
|