vinD27/stock_sentiment_analysis
By vinD27 · ↓ 2 · ♥ 0 · Updated 2024-12-16
What's in this repo
This page lists the files in vinD27/stock_sentiment_analysis, including deberta_v3_model.onnx, deberta_v3_model_fix.onnx.
- 2 ONNX models (.onnx files)
- 5 files, including 2 .onnx, 1 .md, 1 .json
- Last updated 2024-12-16
ONNX files
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
Stock Sentiment Analysis
This model is a fine-tuned version of microsoft/deberta-v3-base for stock sentiment analysis.
Model Details
- Language: English
- Task: Text Classification (Sentiment Analysis)
- Classes: Positive, Neutral, Negative
Training
- Evaluation Metric: F1 Score
- Training Args: See
training_args.binfor details.
Usage
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("vinD27/stock_sentiment_analysis")
model = AutoModelForSequenceClassification.from_pretrained("vinD27/stock_sentiment_analysis")
text = "The stock market is performing well today."
inputs = tokenizer(text, return_tensors="pt")
outputs = model(**inputs)
print(outputs.logits)Model info
onnx
deberta-v3
text-classification
en
base_model:microsoft/deberta-v3-base
base_model:quantized:microsoft/deberta-v3-base
license:apache-2.0
region:us
↓ 2
♥ 0
Created: 2024-12-09
Updated: 2024-12-16
View on Hugging FaceFiles (5)
.gitattributes
README.md
config.json
deberta_v3_model.onnx
ONNX
deberta_v3_model_fix.onnx
ONNX
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