Text Classification
Transformers
Safetensors
modernbert
code
language-identification
multi-label
llm-guard
encoder
text-embeddings-inference
Instructions to use Accuknoxtechnologies/CodeLanguage-Encoder-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Accuknoxtechnologies/CodeLanguage-Encoder-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Accuknoxtechnologies/CodeLanguage-Encoder-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Accuknoxtechnologies/CodeLanguage-Encoder-v1") model = AutoModelForSequenceClassification.from_pretrained("Accuknoxtechnologies/CodeLanguage-Encoder-v1") - Notebooks
- Google Colab
- Kaggle
| { | |
| "base_model": "jhu-clsp/mmBERT-base", | |
| "task": "code-language-identification", | |
| "problem_type": "multi_label_classification", | |
| "labels": [ | |
| "Python", | |
| "JavaScript", | |
| "Java", | |
| "C", | |
| "C++", | |
| "C#", | |
| "Go", | |
| "Rust", | |
| "Kotlin", | |
| "Swift", | |
| "Ruby", | |
| "R", | |
| "Scala", | |
| "Perl", | |
| "Lua", | |
| "Bash", | |
| "PowerShell", | |
| "Batch", | |
| "SQL", | |
| "Dockerfile", | |
| "YAML", | |
| "Makefile", | |
| "Terraform", | |
| "AWK", | |
| "jq" | |
| ], | |
| "max_seq_length": 3072, | |
| "epochs": 2, | |
| "learning_rate": 2e-05, | |
| "threshold": 0.5, | |
| "trained_at": "2026-06-02T09:22:34+00:00" | |
| } |