Fill-Mask
Transformers
Safetensors
English
roberta
genomics
population-genetics
axial-attention
self-supervised
natural-selection
haplotype
Instructions to use leonzong/popf-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use leonzong/popf-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="leonzong/popf-small")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("leonzong/popf-small") model = AutoModelForMaskedLM.from_pretrained("leonzong/popf-small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a1639d7311efc0a7a0f0b23bce494281e6fdf20d4e6a512a63d38a2a46fa3923
- Size of remote file:
- 5.24 kB
- SHA256:
- 238f4f2871731f3669c5542fa1e44dfef1d551a7cc6f64e843c6f15532e7a3d4
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