Instructions to use omarmomen/sf_ip_babylm_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use omarmomen/sf_ip_babylm_1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="omarmomen/sf_ip_babylm_1", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("omarmomen/sf_ip_babylm_1", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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The model is trained on the BabyLM 10M dataset, with a RobertaTokenizer pretrained on the BabyLM 10M dataset with 16K tokens (https://huggingface.co/omarmomen/babylm_bpe_tokenizer_16k).
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The model is trained on the BabyLM 10M dataset, with a RobertaTokenizer pretrained on the BabyLM 10M dataset with 16K tokens (https://huggingface.co/omarmomen/babylm_bpe_tokenizer_16k).
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https://arxiv.org/abs/2403.09714
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