Text Classification
Transformers
ONNX
Safetensors
modernbert
code
programming-language-identification
language-detection
text-embeddings-inference
Instructions to use FrameByFrame/programming-language-identification-100plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use FrameByFrame/programming-language-identification-100plus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="FrameByFrame/programming-language-identification-100plus")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("FrameByFrame/programming-language-identification-100plus") model = AutoModelForSequenceClassification.from_pretrained("FrameByFrame/programming-language-identification-100plus") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 53c62812e0ff7dcc62d4ac24091979220b14c2e2ecb53dca155b8823a8fa42a7
- Size of remote file:
- 300 MB
- SHA256:
- 11574821c81bab1bf8677e06f2fd9036fbf19f3e714d7e9a2d1bb3ce61e9ea91
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