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 rl/rl_agent.pt from KRISHNAPURI/q-trust-codebert: direct link, hf CLI and curl.
- Browser
- Download file 74 kB
-
https://huggingface.co/KRISHNAPURI/q-trust-codebert/resolve/main/rl/rl_agent.pt
- Command line
-
hf download hf://KRISHNAPURI/q-trust-codebert/rl/rl_agent.pt
-
curl -L -o rl_agent.pt https://huggingface.co/KRISHNAPURI/q-trust-codebert/resolve/main/rl/rl_agent.pt
74 kB
- Xet hash:
- 482a58796e410012ad0ed0cf731e7ec73e690481162f4f7858a4614ed96114fe
- Size of remote file:
- 74 kB
- SHA256:
- cffd9383b0cfa3ddd0ceec0926e09a6682a142ae4f13b79355bc8925422f6ecd
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