Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use sk01/DataFeed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sk01/DataFeed with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="sk01/DataFeed")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("sk01/DataFeed") model = AutoModelForSequenceClassification.from_pretrained("sk01/DataFeed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from sk01/DataFeed: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/sk01/DataFeed/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://sk01/DataFeed@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/sk01/DataFeed/resolve/refs%2Fpr%2F1/pytorch_model.bin
268 MB
- Xet hash:
- de8f55507d3702dc8dd7a675925b96d6a094e75c1309049c35fa43d719526b25
- Size of remote file:
- 268 MB
- SHA256:
- 170a2bf5f086890e05c4f7b19f4e8096e8365b7cbdae47c275609471fa13685f
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