Instructions to use kon172verma/intent-classifier-experiments with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use kon172verma/intent-classifier-experiments with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
metadata
library_name: peft
pipeline_tag: intent-classification
license: apache-2.0
tags:
- peft
- lora
- dora
- lora+
- dora
- adalora
- qlora
- text-classification
- intent-classification
Intent Classifier Experiments
This Hugging Face repo stores all experiment-time adapter artifacts for the intent-classifier project.
Purpose
- Keep every adapter checkpoint produced during fine-tuning.
- Preserve per-experiment traceability across versions.
- Keep release artifacts separate from experimental artifacts.
Layout
- v1.0/
- one folder per experiment run
- naming format:
- {model}{technique}{config}{dataset_size}{YYYYMMDD-HHMMSS}
Each experiment folder can include:
- adapter weights
- tokenizer/config files
- metadata and training outputs
Related repositories
Training code and release models are maintained separately.
- Training code: https://github.com/kon172verma/intent-classifier
- Inference/benchmarking: https://github.com/kon172verma/intent-classifier-inference
- Release: https://huggingface.co/kon172verma/intent-classifier
Versioning
Experiment folders are grouped by release version (for example, v1.0). When a version is finalized, only selected best models are promoted to the release repo.