Instructions to use Taykhoom/SpliceBERT-1024nt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Taykhoom/SpliceBERT-1024nt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Taykhoom/SpliceBERT-1024nt", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Taykhoom/SpliceBERT-1024nt", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a728bf123ee1bfa3c98ff6ccf221c2c9896633723e2519add4741241f7690f64
- Size of remote file:
- 78.9 MB
- SHA256:
- 3785342bb2a4d6e602fcbda35e1c3f1659f78f82ed9b3bdd96cf8f0e6a225b63
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