Instructions to use vinai/phobert-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vinai/phobert-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="vinai/phobert-base")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("vinai/phobert-base") model = AutoModelForMaskedLM.from_pretrained("vinai/phobert-base", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from vinai/phobert-base: direct link, hf CLI and curl.
- Browser
- Download file 543 MB
-
https://huggingface.co/vinai/phobert-base/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://vinai/phobert-base/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/vinai/phobert-base/resolve/main/pytorch_model.bin
543 MB
- Xet hash:
- 48e0cdcde28a0e74968d9f8e855ad70b07e76c11f1f993057e32c1e88057f6f1
- Size of remote file:
- 543 MB
- SHA256:
- a0b0f0912c710147fbaac015b0a4011216a0061a56c03b840b639e40d3bb49cc
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