Instructions to use drexalt/neobert-spladev3-distil with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use drexalt/neobert-spladev3-distil with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="drexalt/neobert-spladev3-distil", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("drexalt/neobert-spladev3-distil", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 33014bb40966c5b8bfad551be83aa449b5e196d8c5fee4291311f5381025b98b
- Size of remote file:
- 981 MB
- SHA256:
- c3045792e56cedb82ff35d260084caf778275f566c0d2890924ece490989800a
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