Instructions to use thorszon/dk_emotion_bert_in_class with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use thorszon/dk_emotion_bert_in_class with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="thorszon/dk_emotion_bert_in_class")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("thorszon/dk_emotion_bert_in_class") model = AutoModelForSequenceClassification.from_pretrained("thorszon/dk_emotion_bert_in_class", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from thorszon/dk_emotion_bert_in_class: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/thorszon/dk_emotion_bert_in_class/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://thorszon/dk_emotion_bert_in_class/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/thorszon/dk_emotion_bert_in_class/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- 409dd86caa695fcb14579c83487edada15c56cfb39fc390b126694a79e1c545c
- Size of remote file:
- 443 MB
- SHA256:
- 06bb743c94b4386d9016e7a9cc1f2344cef84bfbc9838e468f0bc08c8b2a53fe
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