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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from FrameByFrame/programming-language-identification-100plus: direct link, hf CLI and curl.
- Browser
- Download file 299 MB
-
https://huggingface.co/FrameByFrame/programming-language-identification-100plus/resolve/main/model.safetensors
- Command line
-
hf download hf://FrameByFrame/programming-language-identification-100plus/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/FrameByFrame/programming-language-identification-100plus/resolve/main/model.safetensors
299 MB
- Xet hash:
- 63b2eecc61828ec446a48e30ce446efd2abede65df3987571e954775710cc9b6
- Size of remote file:
- 299 MB
- SHA256:
- 52b6b9deceb722e8147f9115c0bf7ab8d7fa2a7a64ce6b63444bb82f8788e09d
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