Instructions to use JasperLS/gelectra-base-injection-pt_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JasperLS/gelectra-base-injection-pt_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="JasperLS/gelectra-base-injection-pt_v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("JasperLS/gelectra-base-injection-pt_v1") model = AutoModelForSequenceClassification.from_pretrained("JasperLS/gelectra-base-injection-pt_v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
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:ee874df8cb003f1dafdcd69ab878d620a103e19c79f6f6892b8fdf7be886901f
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size 439745192
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