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")# pip install -U transformers accelerate # 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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model (#1)
- Adding `safetensors` variant of this model (f9420d55cb981761df76fd98656bb41216c5948c) Co-authored-by: Safetensors convertbot <SFconvertbot@users.noreply.huggingface.co>d8bf31c
-
update class name
7b23d9f -
update AutoModelForSequenceClassification
e826b79 -
update model checkpoint AutoModelForSequenceClassification
011ed9d -
update model checkpoint
c57ccaa -
init commit
d27aa9f -
initial commit
d5f86e8