Fill-Mask
Transformers
PyTorch
xlm-roberta
afrolm
active learning
language modeling
research papers
natural language processing
self-active learning
Instructions to use bonadossou/afrolm_active_learning with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bonadossou/afrolm_active_learning with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="bonadossou/afrolm_active_learning")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("bonadossou/afrolm_active_learning") model = AutoModelForMaskedLM.from_pretrained("bonadossou/afrolm_active_learning") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#4
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:9975515d13e8262341346a39acedd941d71e75bd8f299f5156834ad26a2f51f4
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size 1055713880
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