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")# 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
File size: 406 Bytes
3a2e40e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | {
"add_prefix_space": false,
"backend": "tokenizers",
"bos_token": "<s>",
"cls_token": "<s>",
"eos_token": "</s>",
"errors": "replace",
"is_local": false,
"local_files_only": false,
"mask_token": "<mask>",
"max_len": 512,
"model_max_length": 512,
"pad_token": "<pad>",
"sep_token": "</s>",
"tokenizer_class": "RobertaTokenizer",
"trim_offsets": true,
"unk_token": "<unk>"
}
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