Instructions to use g8a9/roberta-tiny-4l-10M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use g8a9/roberta-tiny-4l-10M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="g8a9/roberta-tiny-4l-10M")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("g8a9/roberta-tiny-4l-10M") model = AutoModelForMaskedLM.from_pretrained("g8a9/roberta-tiny-4l-10M", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files
emissions.csv
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timestamp,experiment_id,project_name,duration,emissions,energy_consumed,country_name,country_iso_code,region,on_cloud,cloud_provider,cloud_region
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2023-02-16T02:41:44,5be41da6-2620-433a-b2a3-a6f9935fc057,codecarbon,10704.811419963837,0.6383280029746623,0.9662350450300994,Italy,ITA,lombardy,N,,
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pytorch_model.bin
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size 380407940
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runs/Feb15_23-43-00_monica.sm.unibocconi.it/events.out.tfevents.1676500999.monica.sm.unibocconi.it.1476666.0
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size 11949
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