Instructions to use UCSYNLP/MyanBERTa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use UCSYNLP/MyanBERTa with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="UCSYNLP/MyanBERTa")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("UCSYNLP/MyanBERTa") model = AutoModelForMaskedLM.from_pretrained("UCSYNLP/MyanBERTa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from UCSYNLP/MyanBERTa: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/UCSYNLP/MyanBERTa/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://UCSYNLP/MyanBERTa/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/UCSYNLP/MyanBERTa/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- b0d8bf6f5a0d5d79df88c2d41c7b9c88d3190129d06857cb84d4549dba2fba87
- Size of remote file:
- 438 MB
- SHA256:
- cc97cb2718560784c99fbde6426de4dcc191d68b67dbe54ccec1084d73851f2e
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