Instructions to use askatasuna/psy_q_a_test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use askatasuna/psy_q_a_test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="askatasuna/psy_q_a_test")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("askatasuna/psy_q_a_test") model = AutoModelForQuestionAnswering.from_pretrained("askatasuna/psy_q_a_test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from askatasuna/psy_q_a_test: direct link, hf CLI and curl.
- Browser
- Download file 561 Bytes
-
https://huggingface.co/askatasuna/psy_q_a_test/resolve/main/config.json
- Command line
-
hf download hf://askatasuna/psy_q_a_test/config.json
-
curl -L -o config.json https://huggingface.co/askatasuna/psy_q_a_test/resolve/main/config.json
561 Bytes
| { | |
| "_name_or_path": "distilbert-base-uncased", | |
| "activation": "gelu", | |
| "architectures": [ | |
| "DistilBertForQuestionAnswering" | |
| ], | |
| "attention_dropout": 0.1, | |
| "dim": 768, | |
| "dropout": 0.1, | |
| "hidden_dim": 3072, | |
| "initializer_range": 0.02, | |
| "max_position_embeddings": 512, | |
| "model_type": "distilbert", | |
| "n_heads": 12, | |
| "n_layers": 6, | |
| "pad_token_id": 0, | |
| "qa_dropout": 0.1, | |
| "seq_classif_dropout": 0.2, | |
| "sinusoidal_pos_embds": false, | |
| "tie_weights_": true, | |
| "torch_dtype": "float32", | |
| "transformers_version": "4.30.2", | |
| "vocab_size": 30522 | |
| } | |