Instructions to use voidful/albert_chinese_small_sentiment with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use voidful/albert_chinese_small_sentiment with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="voidful/albert_chinese_small_sentiment")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("voidful/albert_chinese_small_sentiment") model = AutoModelForSequenceClassification.from_pretrained("voidful/albert_chinese_small_sentiment") - Inference
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 0407e6817eeacea4b1e6584b43694220ab397c983156880f4eff752fe81c7fa7
- Size of remote file:
- 19 MB
- SHA256:
- 18cb481fd96d4b2ad4a6cd42dbadee2c61b05152c0bb1031666c4338afec0986
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