Instructions to use Sefika/bert_large_baseline_1_6 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sefika/bert_large_baseline_1_6 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sefika/bert_large_baseline_1_6")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sefika/bert_large_baseline_1_6") model = AutoModelForSequenceClassification.from_pretrained("Sefika/bert_large_baseline_1_6") - Notebooks
- Google Colab
- Kaggle
Upload BertForSequenceClassification
Browse files- config.json +2 -34
- model.safetensors +1 -1
config.json
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"label2id": {
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"LABEL_0": 0,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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"initializer_range": 0.02,
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"intermediate_size": 4096,
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"label2id": {
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"LABEL_0": 0,
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"layer_norm_eps": 1e-12,
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"max_position_embeddings": 512,
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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size 1340712968
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version https://git-lfs.github.com/spec/v1
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size 1340712968
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