Instructions to use Techiiot/sentiment-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Techiiot/sentiment-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Techiiot/sentiment-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Techiiot/sentiment-model") model = AutoModelForSequenceClassification.from_pretrained("Techiiot/sentiment-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Techiiot/sentiment-model: direct link, hf CLI and curl.
- Browser
- Download file 5.2 kB
-
https://huggingface.co/Techiiot/sentiment-model/resolve/main/training_args.bin
- Command line
-
hf download hf://Techiiot/sentiment-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Techiiot/sentiment-model/resolve/main/training_args.bin
5.2 kB
- Xet hash:
- e4054d60545459d40754fba653800a7de5afd30b70b46aaa1ce2e037f59c056c
- Size of remote file:
- 5.2 kB
- SHA256:
- d0ac83f5b168ad4d67a80a0e3c6c27840c69616dbf941f72c1814725449a416d
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