Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Kamer/Basic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Kamer/Basic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Kamer/Basic")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Kamer/Basic") model = AutoModelForSequenceClassification.from_pretrained("Kamer/Basic", 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:d873eef2cda45a3cb577eb15b14803c62ea9c5709ca08341ac4b554d18cd8172
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size 267887936
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