Instructions to use ppower1/huggingface_train with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ppower1/huggingface_train with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ppower1/huggingface_train")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ppower1/huggingface_train") model = AutoModelForSequenceClassification.from_pretrained("ppower1/huggingface_train") - 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:e663f9a6e8cd9fd587966a3e2a1f57910bb84563538d8387746b60053231fc45
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size 267832560
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