Instructions to use Jeevesh8/sMLM-256-LF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Jeevesh8/sMLM-256-LF with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="Jeevesh8/sMLM-256-LF")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("Jeevesh8/sMLM-256-LF") model = AutoModelForMaskedLM.from_pretrained("Jeevesh8/sMLM-256-LF", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 134 Bytes
7d56118 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:88f2dfb08b5ab31efa34c60ee52709d99b8daa42fd3f480650c3901f3cc36f7b
size 595034203
|