Instructions to use TheJournal/good_sentiment_model2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheJournal/good_sentiment_model2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TheJournal/good_sentiment_model2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("TheJournal/good_sentiment_model2") model = AutoModelForSequenceClassification.from_pretrained("TheJournal/good_sentiment_model2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
Verified signatureThis is an automated PR created with https://huggingface.co/spaces/safetensors/convert This new file is equivalent to `pytorch_model.bin` but safe in the sense that no arbitrary code can be put into it. These files also happen to load much faster than their pytorch counterpart: https://colab.research.google.com/github/huggingface/notebooks/blob/main/safetensors_doc/en/speed.ipynb The widgets on your model page will run using this model even if this is not merged making sure the file actually works. If you find any issues: please report here: https://huggingface.co/spaces/safetensors/convert/discussions Feel free to ignore this PR.5ae5868
-
Upload special_tokens_map.json with huggingface_hub
8bab99f -
Upload tokenizer_config.json with huggingface_hub
3894417 -
Upload pytorch_model.bin with huggingface_hub
9b2703d -
Upload config.json with huggingface_hub
a2941eb -
Upload vocab.txt with huggingface_hub
3dc5936 -
Upload tokenizer.json with huggingface_hub
8c67461 -
initial commit
236df0e