Instructions to use Taykhoom/SpliceBERT-510nt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Taykhoom/SpliceBERT-510nt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Taykhoom/SpliceBERT-510nt", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("Taykhoom/SpliceBERT-510nt", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 321577bc771637dc77a3d6b828593742602f5960eee09995b01c9639c49806e2
- Size of remote file:
- 77.8 MB
- SHA256:
- f0bb0a72f67b8dc7e759d181af72367891ff044a0eaed6c76209518105c6017c
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