Instructions to use zq2186/model_da_small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zq2186/model_da_small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="zq2186/model_da_small")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("zq2186/model_da_small") model = AutoModelForSequenceClassification.from_pretrained("zq2186/model_da_small", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a2696148ab7c00d15dbaf1e8d734587471e134effbe112e9cfde18cd98be697f
- Size of remote file:
- 3.06 kB
- SHA256:
- 37b1ab3d5a750e94eac317cbae07dac0fd08001c236db0deff366e661bfef2d3
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.