Text Classification
Transformers
Safetensors
code
roberta
codebert
vulnerability-detection
cybersecurity
software-security
static-analysis
text-embeddings-inference
Instructions to use Khansa-saAI-29/final-codebert-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Khansa-saAI-29/final-codebert-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Khansa-saAI-29/final-codebert-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Khansa-saAI-29/final-codebert-model") model = AutoModelForSequenceClassification.from_pretrained("Khansa-saAI-29/final-codebert-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from Khansa-saAI-29/final-codebert-model: direct link, hf CLI and curl.
- Browser
- Download file 499 MB
-
https://huggingface.co/Khansa-saAI-29/final-codebert-model/resolve/main/model.safetensors
- Command line
-
hf download hf://Khansa-saAI-29/final-codebert-model/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/Khansa-saAI-29/final-codebert-model/resolve/main/model.safetensors
499 MB
- Xet hash:
- 5fe02c2fed9e54541b32e6e94bdbf2549c584d7328bc6f62b2f2ac34ad693689
- Size of remote file:
- 499 MB
- SHA256:
- c2bc2bc5b7c90e2a6754a1f223e9a92f3c441f6ef4de59f713ec5b31a1eaebda
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.