Fill-Mask
Transformers
TensorFlow
English
bert
license
sentence-classification
scancode
license-compliance
Instructions to use ayansinha/false-positives-scancode-bert-base-uncased-L8-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ayansinha/false-positives-scancode-bert-base-uncased-L8-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="ayansinha/false-positives-scancode-bert-base-uncased-L8-1")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("ayansinha/false-positives-scancode-bert-base-uncased-L8-1") model = AutoModelForMaskedLM.from_pretrained("ayansinha/false-positives-scancode-bert-base-uncased-L8-1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update tf_model.h5
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tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:982e7a5172f0e2232fc81b01469b053ce3a8ece2efa45b1482b10dc2182266ed
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size 438206192
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