Text Classification
Transformers
Safetensors
PEFT
English
mpnet
patents
green-tech
qlora
sequence-classification
Eval Results (legacy)
text-embeddings-inference
Instructions to use CTB2001/Assignment_3_Model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CTB2001/Assignment_3_Model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CTB2001/Assignment_3_Model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("CTB2001/Assignment_3_Model") model = AutoModelForSequenceClassification.from_pretrained("CTB2001/Assignment_3_Model") - PEFT
How to use CTB2001/Assignment_3_Model with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0e60fc71c458be5b27db658063c52174a4ba454e08334fa2a8499f729921041b
- Size of remote file:
- 438 MB
- SHA256:
- a62f3eaa65e5b6ff653583ee4fe27d1bb9ba2635728824c27616ab127955a282
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