Text Classification
Transformers
TensorBoard
ONNX
Safetensors
PyTorch
English
distilbert
movie-review-sentiment
BertForSequenceClassification
Generated from Trainer
text-embeddings-inference
Instructions to use pitangent-ds/distilbert-base-imdb with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pitangent-ds/distilbert-base-imdb with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="pitangent-ds/distilbert-base-imdb")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("pitangent-ds/distilbert-base-imdb") model = AutoModelForSequenceClassification.from_pretrained("pitangent-ds/distilbert-base-imdb", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model_optimized_quantized.onnx from pitangent-ds/distilbert-base-imdb: direct link, hf CLI and curl.
- Browser
- Download file 66 MB
-
https://huggingface.co/pitangent-ds/distilbert-base-imdb/resolve/main/model_optimized_quantized.onnx
- Command line
-
hf download hf://pitangent-ds/distilbert-base-imdb/model_optimized_quantized.onnx
-
curl -L -o model_optimized_quantized.onnx https://huggingface.co/pitangent-ds/distilbert-base-imdb/resolve/main/model_optimized_quantized.onnx
66 MB
- Xet hash:
- 6d9094e7bd265a3389871fe9b2685dbb2f6afe3b5e3ea27807f34573eaa81439
- Size of remote file:
- 66 MB
- SHA256:
- 6d57a81ddb8dacf4f5f9d03326ae9f2e74dc226e8e726503b2dec69b3db65dad
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