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
| { | |
| "n": 500, | |
| "threshold": 0.5, | |
| "max_seq_length": 3072, | |
| "is_valid_accuracy": 0.958, | |
| "category_set_accuracy": 0.82, | |
| "micro_f1": 0.8976234003656307, | |
| "macro_f1": 0.8954906015550027, | |
| "per_language_f1": { | |
| "Python": 0.8627450980392157, | |
| "JavaScript": 0.8163265306122449, | |
| "Java": 0.9166666666666666, | |
| "C": 0.8636363636363636, | |
| "C++": 0.9361702127659575, | |
| "C#": 0.926829268292683, | |
| "Go": 0.918918918918919, | |
| "Rust": 0.9811320754716981, | |
| "Kotlin": 1.0, | |
| "Swift": 0.9166666666666666, | |
| "Ruby": 0.9, | |
| "R": 0.9056603773584906, | |
| "Scala": 0.7619047619047619, | |
| "Perl": 0.8571428571428571, | |
| "Lua": 0.8666666666666667, | |
| "Bash": 0.7222222222222222, | |
| "PowerShell": 0.8333333333333334, | |
| "Batch": 0.9019607843137255, | |
| "SQL": 0.9803921568627451, | |
| "Dockerfile": 0.9767441860465116, | |
| "YAML": 0.9545454545454546, | |
| "Makefile": 0.8780487804878049, | |
| "Terraform": 0.8947368421052632, | |
| "AWK": 0.9259259259259259, | |
| "jq": 0.8888888888888888 | |
| }, | |
| "latency_ms_per_example": { | |
| "mean": 2.3932456970214844, | |
| "p95": 3.833106905221939, | |
| "device": "cuda:0" | |
| }, | |
| "base_model": "jhu-clsp/mmBERT-base", | |
| "epochs": 2 | |
| } |