Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use chriskim2273/IOTNation_Classification_Model_0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chriskim2273/IOTNation_Classification_Model_0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="chriskim2273/IOTNation_Classification_Model_0.1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("chriskim2273/IOTNation_Classification_Model_0.1") model = AutoModelForSequenceClassification.from_pretrained("chriskim2273/IOTNation_Classification_Model_0.1", 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 sha256:0cd96a186170b52ef9e3f3b05d3e280a4b402c66cd7f1e56a3665c24594d77c4
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size 263144680
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