Instructions to use DedsecurityAI/DPTb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DedsecurityAI/DPTb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="DedsecurityAI/DPTb")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("DedsecurityAI/DPTb") model = AutoModel.from_pretrained("DedsecurityAI/DPTb") - Notebooks
- Google Colab
- Kaggle
Commit ·
e14ba08
1
Parent(s): ebf37ca
Create config.json
Browse files- config.json +24 -0
config.json
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{
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"apply_residual_connection_post_layernorm": false,
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"attention_dropout": 0.0,
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"architectures": [
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"BloomModel"
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],
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"attention_softmax_in_fp32": true,
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"pad_token_id": 3,
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"bos_token_id": 1,
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"eos_token_id": 2,
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"hidden_dropout": 0.0,
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-05,
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"masked_softmax_fusion": true,
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"model_type": "bloom",
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"n_embed": 14336,
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"n_layer": 70,
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"num_attention_heads": 112,
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"pretraining_tp": 4,
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"slow_but_exact": false,
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"transformers_version": "4.21.0",
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"use_cache": true,
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"vocab_size": 250880
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}
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