Instructions to use Hartunka/bert_base_km_10_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Hartunka/bert_base_km_10_v2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, DistilBertForLDAMaskedLM tokenizer = AutoTokenizer.from_pretrained("Hartunka/bert_base_km_10_v2") model = DistilBertForLDAMaskedLM.from_pretrained("Hartunka/bert_base_km_10_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
End of training
Verified signature1c8e9e1 -
Model save
Verified signatureab5026f -
Training in progress, step 59550
Verified signaturec67df9c -
Training in progress, step 50000
Verified signatureccf307a -
Training in progress, step 40000
Verified signaturec5d6a41 -
Training in progress, step 30000
Verified signaturea42883c -
Training in progress, step 20000
Verified signaturedcd625d
-
Training in progress, step 10000
Verified signature4cf4f3f
-
End of training
Verified signaturebc88ffc -
Model save
Verified signature2aca412 -
Training in progress, step 59550
Verified signature1431a62 -
Training in progress, step 50000
Verified signaturef245087 -
Training in progress, step 40000
Verified signaturec8192ad -
Training in progress, step 30000
Verified signaturedbc62ee -
Training in progress, step 20000
Verified signatureb6a0575 -
initial commit
Verified signature1bdb61e