Instructions to use Kamer/distilbert_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kamer/distilbert_base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Kamer/distilbert_base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Kamer/distilbert_base") model = AutoModelForSequenceClassification.from_pretrained("Kamer/distilbert_base", 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:a4ac26ddd9e1433ce5b2dcb904b482cf0665ffa7c8862f75916f2862bec601d5
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size 267887936
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