Text Classification
Transformers
Safetensors
English
albert
steam-reviews
BERT
albert-base-v2
sentiment-analysis
constructiveness
gaming
fine-tuned
Eval Results (legacy)
Instructions to use abullard1/albert-v2-steam-review-constructiveness-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abullard1/albert-v2-steam-review-constructiveness-classifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abullard1/albert-v2-steam-review-constructiveness-classifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abullard1/albert-v2-steam-review-constructiveness-classifier") model = AutoModelForSequenceClassification.from_pretrained("abullard1/albert-v2-steam-review-constructiveness-classifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from abullard1/albert-v2-steam-review-constructiveness-classifier: direct link, hf CLI and curl.
- Browser
- Download file 5.24 kB
-
https://huggingface.co/abullard1/albert-v2-steam-review-constructiveness-classifier/resolve/main/training_args.bin
- Command line
-
hf download hf://abullard1/albert-v2-steam-review-constructiveness-classifier/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/abullard1/albert-v2-steam-review-constructiveness-classifier/resolve/main/training_args.bin
5.24 kB
- Xet hash:
- 46b36d3b5ac805aeeb568f19cf8c76d3dcd00270efb0781b903b9d607d9c67c9
- Size of remote file:
- 5.24 kB
- SHA256:
- 0d9c493e6661fa18c0a855ed6539a60b2c9a2dc439c1ab671b1d603d49fa63e8
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