Instructions to use tweettemposhift/topic-topic_random2_seed0-bertweet-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tweettemposhift/topic-topic_random2_seed0-bertweet-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tweettemposhift/topic-topic_random2_seed0-bertweet-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tweettemposhift/topic-topic_random2_seed0-bertweet-base") model = AutoModelForSequenceClassification.from_pretrained("tweettemposhift/topic-topic_random2_seed0-bertweet-base") - Notebooks
- Google Colab
- Kaggle
commit files to HF hub
Browse files- summary.json +1 -0
- training_args.bin +3 -0
summary.json
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{"test/eval_loss": 0.18322181701660156, "test/eval_f1": 0.5533262935586061, "test/eval_f1_macro": 0.12783706682537416, "test/eval_accuracy": 0.35799522673031026, "test/eval_runtime": 2.01, "test/eval_samples_per_second": 208.459, "test/eval_steps_per_second": 13.433}
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:5f10947bd07091c846e9e1ef6ac5ca8134199d9ce5ccb36130bb61161e5386a1
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size 4536
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