Fork, by Memoize Labs (V0.0.1.2)
Report bugs and get support at contact@memoizelabs.com
Installation
For first-time users, begin by running:
foo@user:~$ pip install memoizelabs
For upgrading to the latest version, upgrade to the latest version by running:
foo@user:~$ pip install --upgrade memoizelabs
Usage
Methods
Fork.fork(id, file_paths, isolated_voice_path, description='')
- Parameters:
- id (str): the user-specified ID of the model.
- file_paths (str array): a string of file paths containing objects to fine tune on. These can be .txt, .mp3, or .mp4 files.
- isolated_voice_path (str): a path to a .mp3 file containing a clean recording of the target at least 30 seconds in length, used to pre-process submitted files and identify the target's voice within them before finetuning for better results.
- description (str, optional): a description of the target (ex: An elderly woman with a deep, soothing voice, a British accent, and a witty sense of humor).
StateMachine.state()
- Returns:
- The current state of the state machine, one of INIT, PRE-OP, OPERATIONAL, or FAULT.
StateMachine.errors()
- Returns:
- Array of errors
Classes
Fork(api_key)
- Parameters:
- api_key (str): your Memoize Labs Fork API key. Get one at memoizelabs.com/fork
StateMachine() : A state machine for using real time interactive features with low latency and continous connection to the server.
- States:
- INIT: the initialization state of the state machine. The state machine performs initial checks to confirm access to an audio device and wi-fi, then transitions to PRE-OP if checks pass or FAULT if an issue is detected.
- PRE-OP: the state machine is ready to begin live streaming of data upon command.
- OPERATIONAL: the state machine is connected and exchanging live streams with the server.
- FAULT: the fault state of the state machine. Once the causal errors are resolved, the user must transition the state machine back to INIT state by calling
StateMachine.transition_state(INIT)and initialization checks will be re-run.
Metadata
Release files for memoizelabs 0.0.1.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| memoizelabs-0.0.1.2.tar.gz | 4.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| memoizelabs-0.0.1.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 10.1 kB
Release files / memoizelabs-0.0.1.2.tar.gz
| Download URL | memoizelabs-0.0.1.2.tar.gz |
|---|---|
| Size | 4.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.0 CPython/3.12.2
|
Release files / memoizelabs-0.0.1.2-py3-none-any.whl
| Download URL | memoizelabs-0.0.1.2-py3-none-any.whl |
|---|---|
| Size | 5.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/5.1.0 CPython/3.12.2
|