Fill-Mask
Transformers
Safetensors
PyTorch
Baluchi
xlm-roberta
balochi
low-resource
masked-language-modeling
domain-adaptive-pretraining
Eval Results (legacy)
Instructions to use shahbakhsh/BalBERT with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shahbakhsh/BalBERT with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="shahbakhsh/BalBERT")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("shahbakhsh/BalBERT") model = AutoModelForMaskedLM.from_pretrained("shahbakhsh/BalBERT", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 54ce180af5d515722612996235300037b764357ba7c59b1e735aa6f308fd1098
- Size of remote file:
- 5.27 kB
- SHA256:
- 60e5f8dd46572ad57b2186106eb59e2db33db0648038fa7c0833fe8a126fe52f
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