Instructions to use distilbert/distilbert-base-cased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use distilbert/distilbert-base-cased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="distilbert/distilbert-base-cased")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("distilbert/distilbert-base-cased") model = AutoModelForMaskedLM.from_pretrained("distilbert/distilbert-base-cased") - Inference
- Notebooks
- Google Colab
- Kaggle
Fix architectures in config.json
#6
by Xenova HF Staff - opened
- config.json +3 -0
config.json
CHANGED
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@@ -1,5 +1,8 @@
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{
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"activation": "gelu",
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"attention_dropout": 0.1,
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"dim": 768,
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"dropout": 0.1,
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{
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"activation": "gelu",
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"architectures": [
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"DistilBertForMaskedLM"
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],
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"attention_dropout": 0.1,
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"dim": 768,
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"dropout": 0.1,
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