mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-26 22:30:32 +01:00
672a6f1018
Main thing is that the default output filename will take this form
{name}{parameters}{finetune}{version}{encoding}{kind}
In addition this add and remove some entries in the KV store and adds a metadata class with automatic heuristics capability to derive some values based on model card content
* No Change:
- Internal GGUF Spec
- `general.architecture`
- `general.quantization_version`
- `general.alignment`
- `general.file_type`
- General Model Details
- `general.name`
- `general.author`
- `general.version`
- `general.description`
- Licensing details
- `general.license`
- Typically represents the converted GGUF repo (Unless made from scratch)
- `general.url`
- Model Source during conversion
- `general.source.url`
* Removed:
- Model Source during conversion
- `general.source.huggingface.repository`
* Added:
- General Model Details
- `general.organization`
- `general.finetune`
- `general.basename`
- `general.quantized_by`
- `general.size_label`
- Licensing details
- `general.license.name`
- `general.license.link`
- Typically represents the converted GGUF repo (Unless made from scratch)
- `general.doi`
- `general.uuid`
- `general.repo_url`
- Model Source during conversion
- `general.source.doi`
- `general.source.uuid`
- `general.source.repo_url`
- Base Model Source
- `general.base_model.count`
- `general.base_model.{id}.name`
- `general.base_model.{id}.author`
- `general.base_model.{id}.version`
- `general.base_model.{id}.organization`
- `general.base_model.{id}.url` (Model Website/Paper)
- `general.base_model.{id}.doi`
- `general.base_model.{id}.uuid`
- `general.base_model.{id}.repo_url` (Model Source Repository (git/svn/etc...))
- Array based KV stores
- `general.tags`
- `general.languages`
- `general.datasets`
---------
Co-authored-by: compilade <git@compilade.net>
Co-authored-by: Xuan Son Nguyen <thichthat@gmail.com>
91 lines
2.7 KiB
Markdown
91 lines
2.7 KiB
Markdown
## gguf
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This is a Python package for writing binary files in the [GGUF](https://github.com/ggerganov/ggml/pull/302)
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(GGML Universal File) format.
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See [convert_hf_to_gguf.py](https://github.com/ggerganov/llama.cpp/blob/master/convert_hf_to_gguf.py)
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as an example for its usage.
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## Installation
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```sh
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pip install gguf
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```
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## API Examples/Simple Tools
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[examples/writer.py](https://github.com/ggerganov/llama.cpp/blob/master/gguf-py/examples/writer.py) — Generates `example.gguf` in the current directory to demonstrate generating a GGUF file. Note that this file cannot be used as a model.
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[scripts/gguf_dump.py](https://github.com/ggerganov/llama.cpp/blob/master/gguf-py/scripts/gguf_dump.py) — Dumps a GGUF file's metadata to the console.
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[scripts/gguf_set_metadata.py](https://github.com/ggerganov/llama.cpp/blob/master/gguf-py/scripts/gguf_set_metadata.py) — Allows changing simple metadata values in a GGUF file by key.
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[scripts/gguf_convert_endian.py](https://github.com/ggerganov/llama.cpp/blob/master/gguf-py/scripts/gguf_convert_endian.py) — Allows converting the endianness of GGUF files.
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[scripts/gguf_new_metadata.py](https://github.com/ggerganov/llama.cpp/blob/master/gguf-py/scripts/gguf_new_metadata.py) — Copies a GGUF file with added/modified/removed metadata values.
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## Development
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Maintainers who participate in development of this package are advised to install it in editable mode:
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```sh
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cd /path/to/llama.cpp/gguf-py
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pip install --editable .
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```
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**Note**: This may require to upgrade your Pip installation, with a message saying that editable installation currently requires `setup.py`.
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In this case, upgrade Pip to the latest:
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```sh
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pip install --upgrade pip
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```
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## Automatic publishing with CI
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There's a GitHub workflow to make a release automatically upon creation of tags in a specified format.
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1. Bump the version in `pyproject.toml`.
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2. Create a tag named `gguf-vx.x.x` where `x.x.x` is the semantic version number.
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```sh
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git tag -a gguf-v1.0.0 -m "Version 1.0 release"
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```
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3. Push the tags.
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```sh
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git push origin --tags
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```
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## Manual publishing
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If you want to publish the package manually for any reason, you need to have `twine` and `build` installed:
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```sh
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pip install build twine
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```
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Then, follow these steps to release a new version:
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1. Bump the version in `pyproject.toml`.
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2. Build the package:
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```sh
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python -m build
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```
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3. Upload the generated distribution archives:
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```sh
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python -m twine upload dist/*
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```
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## Run Unit Tests
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From root of this repository you can run this command to run all the unit tests
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```bash
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python -m unittest discover ./gguf-py -v
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```
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## TODO
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- [ ] Include conversion scripts as command line entry points in this package.
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