Instructions to use martincc98/bert_A3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use martincc98/bert_A3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="martincc98/bert_A3")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("martincc98/bert_A3") model = AutoModelForMaskedLM.from_pretrained("martincc98/bert_A3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload DistilBertForTokenClassification
Browse files- config.json +1 -1
- model.safetensors +1 -1
config.json
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"_name_or_path": "
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"activation": "gelu",
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"architectures": [
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"DistilBertForTokenClassification"
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{
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"_name_or_path": "distilbert-base-uncased",
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"activation": "gelu",
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"architectures": [
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"DistilBertForTokenClassification"
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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version https://git-lfs.github.com/spec/v1
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oid sha256:0dbc55882be7589bf6764cc6c125e1b1b12520b54cec410fd4296afeb841b100
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size 265648432
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