Instructions to use MarcoYuTono/huawei-noahTinyBERT_General_6L_768_HotpotQA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MarcoYuTono/huawei-noahTinyBERT_General_6L_768_HotpotQA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="MarcoYuTono/huawei-noahTinyBERT_General_6L_768_HotpotQA")# Load model directly from transformers import AutoTokenizer, AutoModelForQuestionAnswering tokenizer = AutoTokenizer.from_pretrained("MarcoYuTono/huawei-noahTinyBERT_General_6L_768_HotpotQA") model = AutoModelForQuestionAnswering.from_pretrained("MarcoYuTono/huawei-noahTinyBERT_General_6L_768_HotpotQA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 710 Bytes
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"_name_or_path": "huawei-noah/TinyBERT_General_6L_768D",
"architectures": [
"BertForQuestionAnswering"
],
"attention_probs_dropout_prob": 0.1,
"cell": {},
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"hidden_size": 768,
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"intermediate_size": 3072,
"layer_norm_eps": 1e-12,
"max_position_embeddings": 512,
"model_type": "bert",
"num_attention_heads": 12,
"num_hidden_layers": 6,
"pad_token_id": 0,
"position_embedding_type": "absolute",
"pre_trained": "",
"structure": [],
"torch_dtype": "float32",
"transformers_version": "4.20.1",
"type_vocab_size": 2,
"use_cache": true,
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}
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