Instructions to use abigailp/m3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abigailp/m3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abigailp/m3")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abigailp/m3") model = AutoModelForSequenceClassification.from_pretrained("abigailp/m3") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:49454248f6c4dd0c339d7642f52af990cd28c6e085eb53234fa38e877c9bb0df
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size 267832560
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