Instructions to use addy88/programming-lang-identifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use addy88/programming-lang-identifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="addy88/programming-lang-identifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("addy88/programming-lang-identifier") model = AutoModelForSequenceClassification.from_pretrained("addy88/programming-lang-identifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from addy88/programming-lang-identifier: direct link, hf CLI and curl.
- Browser
- Download file 334 MB
-
https://huggingface.co/addy88/programming-lang-identifier/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://addy88/programming-lang-identifier/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/addy88/programming-lang-identifier/resolve/main/pytorch_model.bin
334 MB
- Xet hash:
- f377157c87818c1f7734611255d805fe6781d59d79c5b1c868e486b8f261da0f
- Size of remote file:
- 334 MB
- SHA256:
- b3b7b5b94ef3e1eb7c219ae99129287ab1c3bf42a984154b48363000c6b4330c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.