File size: 2,317 Bytes
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language:
- en
- zh
license: other
license_name: source-specific-licenses
license_link: https://github.com/eyanhe/NLP-Course-Project-LFTC/blob/main/assets.lock.json
task_categories:
- text-classification
tags:
- checkpoints
- reproducibility
---
# LFTC: datasets and checkpoints
Uploaded and content-verified.
This is the large-asset companion to [NLP-Course-Project-LFTC](https://github.com/eyanhe/NLP-Course-Project-LFTC).
Code, reports, figures, PowerPoint, Excel, metrics and per-example predictions are in GitHub.
The local snapshot contains **2,044 asset files**, **56,530,278,162 bytes**.
Files under `artifacts/` retain their original project-relative paths, including datasets, prepared inputs, pretrained models, final/local checkpoints and feature bundles. Historical `.cache/` candidate checkpoints are stored under `artifacts/legacy-candidates/`, since the Hub reserves `.cache/` paths.
[artifact-manifest.json](artifact-manifest.json) records paths, sizes, SHA256 values and verification status.
## Restore
```sh
hf download Eyanhe/LFTC_Dataset_And_Checkpoints --repo-type dataset --local-dir ../lftc-assets
```
Merge the downloaded files into the GitHub project root according to the manifest's original `path` field. In particular, restore `artifacts/legacy-candidates/` to the original `.cache/` directory; other `artifacts/` paths map directly to the project root.
The snapshot covers files actually present on the local workstation; it does not claim that every checkpoint produced on the training cluster has been downloaded.
## Provenance and scope
The study has 428 completed v3 records, including 232 current-research records, 226 with V metrics and 42 fixed models with formal Q evaluations.
These counts describe experiments, not a promise of 428 complete checkpoint folders. The original 2,859-item matrix was not fully executed.
Each original dataset and pretrained model retains its own source-specific license. The mixed collection is not relicensed under one blanket license.
Original asset locks and model/readme metadata are retained at their corresponding paths and in GitHub.
Local credentials, runtimes, private cluster-login helpers, regenerable MinHash work cache and duplicate transfer archives are outside this publication.
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