Instructions to use MENG21/results_distilbert-base-uncased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MENG21/results_distilbert-base-uncased with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MENG21/results_distilbert-base-uncased")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MENG21/results_distilbert-base-uncased") model = AutoModelForSequenceClassification.from_pretrained("MENG21/results_distilbert-base-uncased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from MENG21/results_distilbert-base-uncased: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/MENG21/results_distilbert-base-uncased/resolve/main/training_args.bin
- Command line
-
hf download hf://MENG21/results_distilbert-base-uncased/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/MENG21/results_distilbert-base-uncased/resolve/main/training_args.bin
4.73 kB
- Xet hash:
- 930a96ff6e8f306c98735fdd7d525acea391fc6b0603a4437b0697459e80b2bd
- Size of remote file:
- 4.73 kB
- SHA256:
- 6e1a55b0f8db6080db6b9fb328c061a06b86eff36221f96137c0e6c6e7df7409
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