Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use tingchih/1023 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tingchih/1023 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tingchih/1023")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tingchih/1023") model = AutoModelForSequenceClassification.from_pretrained("tingchih/1023", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from tingchih/1023: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/tingchih/1023/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://tingchih/1023/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/tingchih/1023/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 977197f8b0e4712e0b7da14b435c89ae5b98d42bf024db7f867fe55d118e307c
- Size of remote file:
- 268 MB
- SHA256:
- 1be1a6c5fb2bb99cf7f8e7045fde2f31f53ac777d1048c6c17456cbb693c4357
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