Instructions to use fernandals/distilbert_ufrn_posts with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fernandals/distilbert_ufrn_posts with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="fernandals/distilbert_ufrn_posts")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("fernandals/distilbert_ufrn_posts") model = AutoModelForSequenceClassification.from_pretrained("fernandals/distilbert_ufrn_posts", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from fernandals/distilbert_ufrn_posts: direct link, hf CLI and curl.
- Browser
- Download file 4.16 kB
-
https://huggingface.co/fernandals/distilbert_ufrn_posts/resolve/main/training_args.bin
- Command line
-
hf download hf://fernandals/distilbert_ufrn_posts/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/fernandals/distilbert_ufrn_posts/resolve/main/training_args.bin
4.16 kB
- Xet hash:
- 60c9014fd8404673d4afc07cbd9031b1b26ef97eda64651443fbbd436ef2f420
- Size of remote file:
- 4.16 kB
- SHA256:
- a16eb408e690c72498a4d3ad088f8b433c3812a4d6a70c254478f4a3b8c9aca9
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