Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use logiczmaksimka/finetuned_distilbert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use logiczmaksimka/finetuned_distilbert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="logiczmaksimka/finetuned_distilbert-base-uncased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("logiczmaksimka/finetuned_distilbert-base-uncased") model = AutoModelForSequenceClassification.from_pretrained("logiczmaksimka/finetuned_distilbert-base-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from logiczmaksimka/finetuned_distilbert-base-uncased: direct link, hf CLI and curl.
- Browser
- Download file 4.54 kB
-
https://huggingface.co/logiczmaksimka/finetuned_distilbert-base-uncased/resolve/main/training_args.bin
- Command line
-
hf download hf://logiczmaksimka/finetuned_distilbert-base-uncased/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/logiczmaksimka/finetuned_distilbert-base-uncased/resolve/main/training_args.bin
4.54 kB
- Xet hash:
- 4382cd4b425269fa0c1d60d0e51f8be164d447a6e7bfdb37e959d139349de895
- Size of remote file:
- 4.54 kB
- SHA256:
- 73dde1fee856dbf79c67d579b118ebfda555fc7ea81181af6a4a1854e41f84e5
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