Instructions to use microsoft/deberta-v3-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/deberta-v3-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="microsoft/deberta-v3-small")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("microsoft/deberta-v3-small", dtype="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
File size: 578 Bytes
52978a1 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"model_type": "deberta-v2",
"attention_probs_dropout_prob": 0.1,
"hidden_act": "gelu",
"hidden_dropout_prob": 0.1,
"hidden_size": 768,
"initializer_range": 0.02,
"intermediate_size": 3072,
"max_position_embeddings": 512,
"relative_attention": true,
"position_buckets": 256,
"norm_rel_ebd": "layer_norm",
"share_att_key": true,
"pos_att_type": "p2c|c2p",
"layer_norm_eps": 1e-7,
"max_relative_positions": -1,
"position_biased_input": false,
"num_attention_heads": 12,
"num_hidden_layers": 6,
"type_vocab_size": 0,
"vocab_size": 128100
}
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