Instructions to use abcdda/text_analysis with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abcdda/text_analysis with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abcdda/text_analysis")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abcdda/text_analysis") model = AutoModelForSequenceClassification.from_pretrained("abcdda/text_analysis", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from abcdda/text_analysis: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/abcdda/text_analysis/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://abcdda/text_analysis/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/abcdda/text_analysis/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 3b72020e98f86c4a9359f38037ba8172bd45db9ba103a91a4806f25993f70359
- Size of remote file:
- 268 MB
- SHA256:
- aedcc46c262d17cc199846b43bf2bc61fec46d9de2d5576f1780e04d40232d82
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