Instructions to use mgh6/TCS_MLM_All with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mgh6/TCS_MLM_All with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mgh6/TCS_MLM_All")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mgh6/TCS_MLM_All") model = AutoModelForMaskedLM.from_pretrained("mgh6/TCS_MLM_All") - Notebooks
- Google Colab
- Kaggle
Ctrl+K
- Jun03_03-45-38_training-full-0-0
- Jun03_03-54-04_training-full-0-0
- Jun03_03-56-12_training-full-0-0
- Jun03_03-58-12_training-full-0-0
- May24_02-34-23_test-training-0-0
- May24_02-39-16_test-training-0-0
- May24_02-41-29_test-training-0-0
- May24_02-42-52_test-training-0-0
- May24_03-01-32_test-training-0-1
- May24_03-07-44_test-training-0-1
- May24_03-11-05_test-training-0-1
- May24_05-02-38_testing-large-0-2
- May28_21-19-49_training-full-0-0
- May28_22-42-13_training-full-0-0
- May28_22-42-54_training-full-0-0
- May29_15-06-36_training-full-0-0
- May29_15-13-27_training-full-0-0
- May29_15-18-00_training-full-0-0
- May30_02-45-22_training-full-0-0
- May30_02-51-39_training-full-0-0
- May30_02-54-12_training-full-0-0
- May30_02-55-43_training-full-0-0
- May30_02-59-16_training-full-0-0
- Oct17_15-55-01_torch-flash-large-0-3