# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("CHIPP-AI/model1")
model = AutoModelForSequenceClassification.from_pretrained("CHIPP-AI/model1", device_map="auto")Quick Links
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Model Details
Model Description
This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
- Developed by: Ruchit Pokhrel and Sandra
- Language(s) (NLP): English
- License: MIT
- Finetuned from model microsoft/deberta-v3-base
Label
0 --> Negative
1--> Neutral
2--> Positive
Metrics on Test Set
Accuracy-0.93
F1-0.92
Precision-0.92
Recall-0.93
MCC-0.81
Eval Loss-0.42
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Base model
microsoft/deberta-v3-base
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="CHIPP-AI/model1")