Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use Ethan615/try with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ethan615/try with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Ethan615/try")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Ethan615/try") model = AutoModelForSequenceClassification.from_pretrained("Ethan615/try", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download run-2/checkpoint-268/optimizer.pt from Ethan615/try: direct link, hf CLI and curl.
- Browser
- Download file 536 MB
-
https://huggingface.co/Ethan615/try/resolve/main/run-2/checkpoint-268/optimizer.pt
- Command line
-
hf download hf://Ethan615/try/run-2/checkpoint-268/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Ethan615/try/resolve/main/run-2/checkpoint-268/optimizer.pt
536 MB
- Xet hash:
- 827d58728d854ac2d78211169e15907c8980cb1ddf1cb5780d2c228794e161d0
- Size of remote file:
- 536 MB
- SHA256:
- d3bf552d7f88b8f1a5fdf2356b75e29966c4b9b2236b51e35360ec66775f46d5
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