Datasets:

PureOne
/

QIRAN-EIDOLITH-v4

# Upload to Hugging Face

Suggested repository slug: `QIRAN-EIDOLITH-v4`  
Suggested type: **Dataset**  
Suggested full title: **QIRĀN–EIDOLITH v4: Hereditary Search, Neutral-Corridor Compilation, and Reusable Evidence for Recursive Self-Improvement**

This is a research-artifact repository with three small browseable metadata configurations. It contains source code, experimental records, and a manuscript. It does not contain pretrained model weights. Uploading is a separate action; preparing this package has not created or published a Hub repository.

## Web interface

1. Create a dataset repository in your own namespace, using the suggested slug or another name you prefer. Select visibility deliberately.
2. Extract the release ZIP locally.
3. Upload **the contents of `QIRAN_EIDOLITH_v4_HuggingFace/`**, so `README.md`, `research/`, `data/`, `docs/`, and `tools/` are at repository root. Uploading only the ZIP will not expose the card or structured indexes.
4. Keep `README.md` as the dataset card. Its YAML selects only the three curated JSONL indexes, avoiding accidental merging of heterogeneous research outputs.
5. Confirm that the manuscript, local evidence links, and claims/metrics/artifacts configurations are visible after upload.
The README can also be copied directly into the card editor if the files are uploaded separately. Leave the mixed-license metadata intact unless you deliberately change the applicable licenses with authority to do so.
## Windows: double-click uploader
1. Extract the complete release ZIP.
2. Double-click `UPLOAD_TO_HUGGINGFACE.bat` in the extracted `QIRAN_EIDOLITH_v4_HuggingFace` folder.
3. The launcher detects Python 3.10+ and installs `huggingface_hub` if missing. If Python is absent it gives installation instructions.
4. The wizard uses a saved Hugging Face login or requests a write token in a hidden prompt. It suggests a repository in your authenticated account; press Enter to accept it or enter another permitted namespace/repository.
5. For a new repository, choose public or private. For an existing one, confirm updating its same-name files; its visibility is preserved.
6. Wait for the upload-complete link. The window remains open so errors stay readable.
An uploader add-on ZIP is also provided for people who already extracted the original release. Extract it into the same parent directory as your existing `QIRAN_EIDOLITH_v4_HuggingFace` folder and allow its updated files to replace the originals. The add-on requires the original research files; use the full corrected ZIP if unsure.
Offline verification, without login or network access:
```bash
python UPLOAD_TO_HUGGINGFACE.py --dry-run
```
Direct command with an explicit target:
```bash
python UPLOAD_TO_HUGGINGFACE.py YOUR_NAMESPACE/QIRAN-EIDOLITH-v4 --public
```
Add `--allow-existing` when intentionally updating an existing dataset from the command line. The uploader selects only checksum-listed files; it does not delete unrelated remote files or store your prompted token in the release.
## Command-line upload
Install the Hub client and authenticate locally:
```bash
python -m pip install -U huggingface_hub
hf auth login
```
Do not put access tokens in the repository, an issue, or a chat message.
From the extracted release root, the included helper defaults to a **private new repository**:
```bash
python tools/upload_hf.py YOUR_NAMESPACE/QIRAN-EIDOLITH-v4
```
To create a public new repository explicitly:
```bash
python tools/upload_hf.py YOUR_NAMESPACE/QIRAN-EIDOLITH-v4 --public
```
The helper verifies local integrity, prints the target and visibility, creates a new dataset repository, and uploads the complete prepared tree in one commit. It refuses an existing repository unless `--allow-existing` is supplied; existing visibility is not changed. Same-name remote files may be replaced on an explicitly allowed update. It does not delete unrelated remote files.
Equivalent CLI steps for a new private repository:
```bash
hf repos create YOUR_NAMESPACE/QIRAN-EIDOLITH-v4 --type dataset --private
hf upload YOUR_NAMESPACE/QIRAN-EIDOLITH-v4 . . --repo-type dataset --commit-message "Release QIRAN-EIDOLITH v4 research artifact"
```
The helper is preferred because it filters local caches and newly generated files. A direct upload of `.` may include later local work. Review the upload selection before using the CLI on a modified tree.
## Description for the repository creation form
QIRĀN–EIDOLITH v4 is a complete finite-model research release on continuation-safe self-modification: hereditary program equivalence, exact neutral-search compilation, state–history recovery, and reusable adaptive evidence. Includes a 125-page manuscript, proof sources, code, raw synthetic experiments, negative controls, and reproduction tools. General recursive superiority remains unestablished.
## Useful topic tags
`recursive-self-improvement`, `self-modifying-systems`, `program-semantics`, `formal-methods`, `adaptive-validation`, `exact-arithmetic`, `markov-chains`, `research-artifact`, `synthetic-data`.
## Official documentation
- [Dataset cards and YAML metadata](https://huggingface.co/docs/hub/datasets-cards)
- [Dataset configurations](https://huggingface.co/docs/hub/datasets-manual-configuration)
- [Hugging Face CLI](https://huggingface.co/docs/huggingface_hub/en/guides/cli)
- [Upload files and folders](https://huggingface.co/docs/huggingface_hub/en/guides/upload)
The examples follow documentation checked on 17 October 2026. Use the installed command’s `--help` if a later client changes its options.

	# Upload to Hugging Face

	Suggested repository slug: `QIRAN-EIDOLITH-v4`
	Suggested type: Dataset
	Suggested full title: QIRĀN–EIDOLITH v4: Hereditary Search, Neutral-Corridor Compilation, and Reusable Evidence for Recursive Self-Improvement

	This is a research-artifact repository with three small browseable metadata configurations. It contains source code, experimental records, and a manuscript. It does not contain pretrained model weights. Uploading is a separate action; preparing this package has not created or published a Hub repository.

	## Web interface

	1. Create a dataset repository in your own namespace, using the suggested slug or another name you prefer. Select visibility deliberately.
	2. Extract the release ZIP locally.
	3. Upload the contents of `QIRAN_EIDOLITH_v4_HuggingFace/`, so `README.md`, `research/`, `data/`, `docs/`, and `tools/` are at repository root. Uploading only the ZIP will not expose the card or structured indexes.
	4. Keep `README.md` as the dataset card. Its YAML selects only the three curated JSONL indexes, avoiding accidental merging of heterogeneous research outputs.
	5. Confirm that the manuscript, local evidence links, and claims/metrics/artifacts configurations are visible after upload.

	The README can also be copied directly into the card editor if the files are uploaded separately. Leave the mixed-license metadata intact unless you deliberately change the applicable licenses with authority to do so.

	## Windows: double-click uploader

	1. Extract the complete release ZIP.
	2. Double-click `UPLOAD_TO_HUGGINGFACE.bat` in the extracted `QIRAN_EIDOLITH_v4_HuggingFace` folder.
	3. The launcher detects Python 3.10+ and installs `huggingface_hub` if missing. If Python is absent it gives installation instructions.
	4. The wizard uses a saved Hugging Face login or requests a write token in a hidden prompt. It suggests a repository in your authenticated account; press Enter to accept it or enter another permitted namespace/repository.
	5. For a new repository, choose public or private. For an existing one, confirm updating its same-name files; its visibility is preserved.
	6. Wait for the upload-complete link. The window remains open so errors stay readable.

	An uploader add-on ZIP is also provided for people who already extracted the original release. Extract it into the same parent directory as your existing `QIRAN_EIDOLITH_v4_HuggingFace` folder and allow its updated files to replace the originals. The add-on requires the original research files; use the full corrected ZIP if unsure.

	Offline verification, without login or network access:

	```bash
	python UPLOAD_TO_HUGGINGFACE.py --dry-run
	```

	Direct command with an explicit target:

	```bash
	python UPLOAD_TO_HUGGINGFACE.py YOUR_NAMESPACE/QIRAN-EIDOLITH-v4 --public
	```

	Add `--allow-existing` when intentionally updating an existing dataset from the command line. The uploader selects only checksum-listed files; it does not delete unrelated remote files or store your prompted token in the release.

	## Command-line upload

	Install the Hub client and authenticate locally:

	```bash
	python -m pip install -U huggingface_hub
	hf auth login
	```

	Do not put access tokens in the repository, an issue, or a chat message.

	From the extracted release root, the included helper defaults to a private new repository:

	```bash
	python tools/upload_hf.py YOUR_NAMESPACE/QIRAN-EIDOLITH-v4
	```

	To create a public new repository explicitly:

	```bash
	python tools/upload_hf.py YOUR_NAMESPACE/QIRAN-EIDOLITH-v4 --public
	```

	The helper verifies local integrity, prints the target and visibility, creates a new dataset repository, and uploads the complete prepared tree in one commit. It refuses an existing repository unless `--allow-existing` is supplied; existing visibility is not changed. Same-name remote files may be replaced on an explicitly allowed update. It does not delete unrelated remote files.

	Equivalent CLI steps for a new private repository:

	```bash
	hf repos create YOUR_NAMESPACE/QIRAN-EIDOLITH-v4 --type dataset --private
	hf upload YOUR_NAMESPACE/QIRAN-EIDOLITH-v4 . . --repo-type dataset --commit-message "Release QIRAN-EIDOLITH v4 research artifact"
	```

	The helper is preferred because it filters local caches and newly generated files. A direct upload of `.` may include later local work. Review the upload selection before using the CLI on a modified tree.

	## Description for the repository creation form

	QIRĀN–EIDOLITH v4 is a complete finite-model research release on continuation-safe self-modification: hereditary program equivalence, exact neutral-search compilation, state–history recovery, and reusable adaptive evidence. Includes a 125-page manuscript, proof sources, code, raw synthetic experiments, negative controls, and reproduction tools. General recursive superiority remains unestablished.

	## Useful topic tags

	`recursive-self-improvement`, `self-modifying-systems`, `program-semantics`, `formal-methods`, `adaptive-validation`, `exact-arithmetic`, `markov-chains`, `research-artifact`, `synthetic-data`.

	## Official documentation

	- [Dataset cards and YAML metadata](https://huggingface.co/docs/hub/datasets-cards)
	- [Dataset configurations](https://huggingface.co/docs/hub/datasets-manual-configuration)
	- [Hugging Face CLI](https://huggingface.co/docs/huggingface_hub/en/guides/cli)
	- [Upload files and folders](https://huggingface.co/docs/huggingface_hub/en/guides/upload)

	The examples follow documentation checked on 17 October 2026. Use the installed command’s `--help` if a later client changes its options.