Instructions to use princeton-nlp/CoFi-SQuAD-s93 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use princeton-nlp/CoFi-SQuAD-s93 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="princeton-nlp/CoFi-SQuAD-s93")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("princeton-nlp/CoFi-SQuAD-s93") model = AutoModelForQuestionAnswering.from_pretrained("princeton-nlp/CoFi-SQuAD-s93", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "_name_or_path": "/checkpoint/mengzhouxia/space2/out/squad/layerdistillv3_prunehidden/squad_l0_headint_nosvd_layerpuning_layerdistillv3_prunehidden_seed57_distilltemp2_pretrain6000_warpup12000_ts0.93_cealpha0.1_20epochs/best", | |
| "architectures": [ | |
| "NewBertForQuestionAnswering" | |
| ], | |
| "attention_probs_dropout_prob": 0.1, | |
| "decompose_qk": false, | |
| "decompose_vo": false, | |
| "do_distill": true, | |
| "do_emb_distill": false, | |
| "do_layer_distill": true, | |
| "do_mha_distill": false, | |
| "do_mha_layer_distill": false, | |
| "gradient_checkpointing": false, | |
| "hidden_act": "gelu", | |
| "hidden_dropout_prob": 0.1, | |
| "hidden_size": 768, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 3072, | |
| "layer_norm_eps": 1e-12, | |
| "max_position_embeddings": 512, | |
| "model_type": "bert", | |
| "num_attention_heads": 12, | |
| "num_hidden_layers": 12, | |
| "output_attentions": true, | |
| "output_hidden_states": true, | |
| "pad_token_id": 0, | |
| "position_embedding_type": "absolute", | |
| "pruned_heads": { | |
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| "qk_denominator": "ori", | |
| "sephidden_pruned": false, | |
| "transform_embedding": false, | |
| "transformers_version": "4.3.2", | |
| "type_vocab_size": 2, | |
| "use_cache": true, | |
| "vocab_size": 30522 | |
| } | |