Instructions to use unmolb/distil_features_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use unmolb/distil_features_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="unmolb/distil_features_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("unmolb/distil_features_v1") model = AutoModelForSequenceClassification.from_pretrained("unmolb/distil_features_v1", device_map="auto") - 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:a855c0a02e0afb6deea4adcc12e3ade74e59d388a893f0aa09b128a200529c40
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size 267875632
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