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
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docs: expand README and HF metadata
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README.md
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---
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license: apache-2.0
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---
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---
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license: apache-2.0
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tags:
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- peft
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- lora
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- dora
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- text-classification
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- intent-classification
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library_name: peft
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---
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# intent-classifier-experiments
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This Hugging Face repo stores all experiment-time adapter artifacts for the
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intent-classifier project.
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## Purpose
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- Keep every adapter checkpoint produced during tuning.
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- Preserve per-experiment traceability across versions.
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- Keep release artifacts separate from experimental artifacts.
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## Layout
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- v1.0/
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- one folder per experiment run
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- naming format:
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- {model}_{technique}_{config}_{dataset_size}_{YYYYMMDD-HHMMSS}
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Each experiment folder can include:
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- adapter weights,
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- tokenizer/config files,
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- metadata and training outputs.
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## Related repositories
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- Training code: https://github.com/kon172verma/intent-classifier
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- Final release models: https://huggingface.co/kon172verma/intent-classifier
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- Inference/benchmarking: https://github.com/kon172verma/intent-classifier-inference
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## Versioning
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Experiment folders are grouped by release version (for example, v1.0).
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When a version is finalized, only selected best models are promoted to the
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release repo.
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