Instructions to use minoosh/finetuned_bert-base-on-IEMOCAP_2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use minoosh/finetuned_bert-base-on-IEMOCAP_2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="minoosh/finetuned_bert-base-on-IEMOCAP_2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("minoosh/finetuned_bert-base-on-IEMOCAP_2") model = AutoModelForSequenceClassification.from_pretrained("minoosh/finetuned_bert-base-on-IEMOCAP_2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from minoosh/finetuned_bert-base-on-IEMOCAP_2: direct link, hf CLI and curl.
- Browser
- Download file 4.03 kB
-
https://huggingface.co/minoosh/finetuned_bert-base-on-IEMOCAP_2/resolve/main/training_args.bin
- Command line
-
hf download hf://minoosh/finetuned_bert-base-on-IEMOCAP_2/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/minoosh/finetuned_bert-base-on-IEMOCAP_2/resolve/main/training_args.bin
4.03 kB
- Xet hash:
- ca51d1e5c3f64c4c5156edb2a04c99b0d8a72dae80f7b633056cd12689a9179f
- Size of remote file:
- 4.03 kB
- SHA256:
- dd656e35c94e95aff63a6a26bbc60ae56ac176bc02e4e782d62ad932ec74dbb0
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