Text Classification
Transformers
ONNX
Safetensors
roberta
code
cryptography
post-quantum
static-analysis
text-embeddings-inference
Instructions to use KRISHNAPURI/q-trust-codebert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KRISHNAPURI/q-trust-codebert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="KRISHNAPURI/q-trust-codebert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("KRISHNAPURI/q-trust-codebert") model = AutoModelForSequenceClassification.from_pretrained("KRISHNAPURI/q-trust-codebert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download crypto_codebert/tokenizer.json from KRISHNAPURI/q-trust-codebert: direct link, hf CLI and curl.
- Browser
- Download file 3.71 MB
-
https://huggingface.co/KRISHNAPURI/q-trust-codebert/resolve/main/crypto_codebert/tokenizer.json
- Command line
-
hf download hf://KRISHNAPURI/q-trust-codebert/crypto_codebert/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/KRISHNAPURI/q-trust-codebert/resolve/main/crypto_codebert/tokenizer.json
3.71 MB
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