Instructions to use tattabio/gLM2_650M_UR50 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tattabio/gLM2_650M_UR50 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tattabio/gLM2_650M_UR50", trust_remote_code=True)# Load model directly from transformers import AutoModelForMaskedLM model = AutoModelForMaskedLM.from_pretrained("tattabio/gLM2_650M_UR50", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
gLM2_650M_UR50
gLM2_650M_UR50 is a fine-tuned vesion of tattabio/gLM2_650M on UniRef50 for 1 epoch.
This is the first stage of finetuning for tattabio/gLM2_650M_embed
- Downloads last month
- 74