Instructions to use omarmomen/transformer_base_final_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use omarmomen/transformer_base_final_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="omarmomen/transformer_base_final_2", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("omarmomen/transformer_base_final_2", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d13bd7147557223f8414a5429af18be86ea30115943d38fd4bbb8240ad62264
- Size of remote file:
- 443 MB
- SHA256:
- 6f1bd8334245a8ebe1db1a2e77e9de14daed9f877b1016c8fa5397151a59fc8c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.