Instructions to use tafseer-nayeem/KidLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tafseer-nayeem/KidLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tafseer-nayeem/KidLM")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tafseer-nayeem/KidLM") model = AutoModelForMaskedLM.from_pretrained("tafseer-nayeem/KidLM", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ad0ab28b876dda32e2c6b3f7ab27656c0330eae856e2ad83ca529efb458f9adf
- Size of remote file:
- 499 MB
- SHA256:
- 6a72fb0fd5b5e2c5b2f2ab0a07dcdca4c764adfec669f0cab3cdc5a4a0248c8c
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