Instructions to use igorktech/hibial-bert-i3-mlm-v0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use igorktech/hibial-bert-i3-mlm-v0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="igorktech/hibial-bert-i3-mlm-v0.1", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("igorktech/hibial-bert-i3-mlm-v0.1", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Update modelling_hibial.py
Browse files- modelling_hibial.py +2 -1
modelling_hibial.py
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@@ -147,7 +147,8 @@ class TransformerEncoderLayer(Module):
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self.self_attn = MultiheadAttention(config.hidden_size,
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config.num_attention_heads,
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dropout=config.attention_probs_dropout_prob
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# Implementation of Feedforward model
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self.linear1 = Linear(config.hidden_size, config.intermediate_size)
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self.dropout = Dropout(config.hidden_dropout_prob)
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self.self_attn = MultiheadAttention(config.hidden_size,
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config.num_attention_heads,
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dropout=config.attention_probs_dropout_prob,
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dtype = torch.float32)
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# Implementation of Feedforward model
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self.linear1 = Linear(config.hidden_size, config.intermediate_size)
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self.dropout = Dropout(config.hidden_dropout_prob)
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