Instructions to use pritamdeka/muril-base-cased-assamese with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pritamdeka/muril-base-cased-assamese with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="pritamdeka/muril-base-cased-assamese")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("pritamdeka/muril-base-cased-assamese") model = AutoModelForMaskedLM.from_pretrained("pritamdeka/muril-base-cased-assamese") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 2.0, | |
| "eval_accuracy": 0.7014180145490598, | |
| "eval_loss": 1.4148573875427246, | |
| "eval_runtime": 102.6889, | |
| "eval_samples": 11967, | |
| "eval_samples_per_second": 116.536, | |
| "eval_steps_per_second": 7.284, | |
| "perplexity": 4.115899445582212, | |
| "total_flos": 1.197729267088466e+17, | |
| "train_loss": 1.6903211268009264, | |
| "train_runtime": 8975.6005, | |
| "train_samples": 227086, | |
| "train_samples_per_second": 50.601, | |
| "train_steps_per_second": 3.163 | |
| } |