Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use marcolatella/Hps_seed1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcolatella/Hps_seed1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcolatella/Hps_seed1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcolatella/Hps_seed1") model = AutoModelForSequenceClassification.from_pretrained("marcolatella/Hps_seed1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from marcolatella/Hps_seed1: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/marcolatella/Hps_seed1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://marcolatella/Hps_seed1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/marcolatella/Hps_seed1/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- ef4a441dc33a5aa38ec6a3696dc08e639b3aeae8fe88f1b409d7c47811acf4d4
- Size of remote file:
- 268 MB
- SHA256:
- 915f54e1794e1ae18de9341cec22ff7ed6a1ad6aa0671c3800a160a1389952a7
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