Text Classification
Transformers
PyTorch
Safetensors
English
distilbert
text Classification
text-embeddings-inference
Instructions to use Sakil/IMDB_URDUSENTIMENT_MODEL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sakil/IMDB_URDUSENTIMENT_MODEL with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Sakil/IMDB_URDUSENTIMENT_MODEL")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Sakil/IMDB_URDUSENTIMENT_MODEL") model = AutoModelForSequenceClassification.from_pretrained("Sakil/IMDB_URDUSENTIMENT_MODEL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from Sakil/IMDB_URDUSENTIMENT_MODEL: direct link, hf CLI and curl.
- Browser
- Download file 322 Bytes
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https://huggingface.co/Sakil/IMDB_URDUSENTIMENT_MODEL/resolve/fb26794612d980917e7d8610d21bdb8a5a5e2eea/README.md
- Command line
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hf download hf://Sakil/IMDB_URDUSENTIMENT_MODEL@fb26794612d980917e7d8610d21bdb8a5a5e2eea/README.md
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curl -L -o README.md https://huggingface.co/Sakil/IMDB_URDUSENTIMENT_MODEL/resolve/fb26794612d980917e7d8610d21bdb8a5a5e2eea/README.md
322 Bytes
| language: | |
| - en | |
| tags: | |
| - text Classification | |
| license: apache-2.0 | |
| widget: | |
| - text: "میں تمہیں پسند کرتا ہوں. </s></s> میں تم سے پیار کرتا ہوں." | |
| * IMDB_URDUSENTIMENT_MODEL | |
| I have used IMDB URDU dataset to create custom model by using DistilBertForSequenceClassification. |