Text Classification
Transformers
Safetensors
distilbert
dia
carbon-footprint
energy-efficiency
sustainability
Instructions to use DIA-MVP/my-bert-sentiment-cpu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use DIA-MVP/my-bert-sentiment-cpu with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="DIA-MVP/my-bert-sentiment-cpu")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("DIA-MVP/my-bert-sentiment-cpu") model = AutoModelForSequenceClassification.from_pretrained("DIA-MVP/my-bert-sentiment-cpu", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Ctrl+K