Downloads · 30 days
19
21% of all-time downloads
Bert_base_finetuned_IMDB
HrishikeshDeore/Bert_base_finetuned_IMDB
Bert_base_finetuned_IMDB is a text classification model from HrishikeshDeore. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
A BERT-based model fine-tuned on the IMDB movie reviews dataset for binary sentiment classification (positive/negative). This model is intended for quick deployment and practical use in applications like review analys…
All-time downloads
89
Public
Parameters
109M
438 MB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors438 MB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Jul 2, 2025
- Updated
- Jul 3, 2025
- SHA
- b7fd1fa5
Try a prompt
Model card
From the Hugging Face model README
Sentiment-BERT-IMDB
A BERT-based model fine-tuned on the IMDB movie reviews dataset for binary sentiment classification (positive/negative). This model is intended for quick deployment and practical use in applications like review analysis, recommendation systems, and content moderation.
Model Details
- Architecture:
bert-base-uncased - Task: Sentiment classification (positive vs. negative)
- Dataset: IMDB
- Classes:
positive,negative - Tokenizer:
bert-base-uncased
How to Use
from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
model = AutoModelForSequenceClassification.from_pretrained("HrishikeshDeore/sentiment-bert-imdb")
tokenizer = AutoTokenizer.from_pretrained("HrishikeshDeore/sentiment-bert-imdb")
nlp = pipeline("sentiment-analysis", model=model, tokenizer=tokenizer)
result = nlp("This movie was absolutely fantastic!")
print(result)
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Languages
- en
- Created
- Jul 2, 2025
- Updated
- Jul 3, 2025