Instructions to use Blablablab/10dimensions-knowledge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Blablablab/10dimensions-knowledge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Blablablab/10dimensions-knowledge")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Blablablab/10dimensions-knowledge") model = AutoModelForSequenceClassification.from_pretrained("Blablablab/10dimensions-knowledge", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Blablablab/10dimensions-knowledge: direct link, hf CLI and curl.
- Browser
- Download file 433 MB
-
https://huggingface.co/Blablablab/10dimensions-knowledge/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://Blablablab/10dimensions-knowledge/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Blablablab/10dimensions-knowledge/resolve/main/pytorch_model.bin
433 MB
- Xet hash:
- b7111a900c00a4ad1ed94fbe6665d6198b882f5664dcc3b3860aff69b97b01fb
- Size of remote file:
- 433 MB
- SHA256:
- aeac8a2c110c65dcaa732d7de02b04a771246ed74b927e80727a2dfdacd036c2
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.