Coder Social home page Coder Social logo

ve-forbryderne / mtj-softtuner Goto Github PK

View Code? Open in Web Editor NEW
26.0 26.0 20.0 429 KB

Create soft prompts for fairseq 13B dense, GPT-J-6B and GPT-Neo-2.7B for free in a Google Colab TPU instance

Home Page: https://henk.tech/softtuner/

License: Apache License 2.0

Jupyter Notebook 21.42% Shell 1.24% Python 77.34%
causal-models colab-notebook fairseq gpt-j gpt-neo jax metaseq nlp nlp-machine-learning prompt-learning prompt-tuning python transformer

mtj-softtuner's People

Contributors

vfbd avatar

Stargazers

 avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar  avatar

Watchers

 avatar  avatar

mtj-softtuner's Issues

Can't connect to TPU

Main KoboldAI has been fixed. Now softtuner needs fixing, because right now it's unusable.

QUERY: running softener locally

Hi.

So is it possible to run softener locally?

Spec: Windows 11 / rtx4090

I cloned the folder onto my windows 11 machine but didn't really make headway. I'll give it another go but was just curious if it could be done. I figured if oobabooga training can be done then soft tuner is a walk in the park so to speak.

mtj-softtuner fails to install + jaxlib requirements not met

Hi.

So I ran the Google Colab and from the first stage I get the jaxlib requirement error and a module error stating mjt-softtuner not installed.

Adding the output below:

Cloning into 'mtj-softtuner'...
remote: Enumerating objects: 831, done.
remote: Counting objects: 100% (323/323), done.
remote: Compressing objects: 100% (123/123), done.
remote: Total 831 (delta 218), reused 267 (delta 192), pack-reused 508
Receiving objects: 100% (831/831), 419.32 KiB | 2.85 MiB/s, done.
Resolving deltas: 100% (501/501), done.
Submodule 'mtj_softtuner/kobold' (https://github.com/henk717/KoboldAI-Client) registered for path 'mtj_softtuner/kobold'
Cloning into '/content/mtj-softtuner/mtj_softtuner/kobold'...
Submodule path 'mtj_softtuner/kobold': checked out '61511a57144689da007fc049f88d5a858d99ab19'
Submodule 'KoboldAI-Horde-Bridge' (https://github.com/db0/KoboldAI-Horde-Bridge) registered for path 'mtj_softtuner/kobold/KoboldAI-Horde-Bridge'
Cloning into '/content/mtj-softtuner/mtj_softtuner/kobold/KoboldAI-Horde-Bridge'...
Submodule path 'mtj_softtuner/kobold/KoboldAI-Horde-Bridge': checked out 'd9014ebac969c0e5c37eb5456deebc3518130391'
WARNING: Skipping mtj-softtuner as it is not installed.
Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/
Processing /content/mtj-softtuner
Preparing metadata (setup.py) ... done
Collecting mesh_transformer@ git+https://github.com/VE-FORBRYDERNE/mesh-transformer-jax#egg=mesh_transformer
Cloning https://github.com/VE-FORBRYDERNE/mesh-transformer-jax to /tmp/pip-install-6o8j4eq4/mesh-transformer_b900c0fde8074c29b6f1f66dab7288b0
Running command git clone --filter=blob:none --quiet https://github.com/VE-FORBRYDERNE/mesh-transformer-jax /tmp/pip-install-6o8j4eq4/mesh-transformer_b900c0fde8074c29b6f1f66dab7288b0
Resolved https://github.com/VE-FORBRYDERNE/mesh-transformer-jax to commit 3febb8e003c18553266b6c2fdcfa60d1647fbc1c
Preparing metadata (setup.py) ... done
Collecting torch<=1.11,>=1.9
Downloading torch-1.11.0-cp310-cp310-manylinux1_x86_64.whl (750.6 MB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 750.6/750.6 MB 2.0 MB/s eta 0:00:00
Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from mtj-softtuner==1.3.6) (1.24.3)
Requirement already satisfied: tqdm in /usr/local/lib/python3.10/dist-packages (from mtj-softtuner==1.3.6) (4.65.0)
Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from mtj-softtuner==1.3.6) (2.27.1)
Collecting optax<=0.1.2,>=0.1.0
Downloading optax-0.1.2-py3-none-any.whl (140 kB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 140.7/140.7 kB 15.9 MB/s eta 0:00:00
Collecting dm-haiku==0.0.5
Downloading dm_haiku-0.0.5-py3-none-any.whl (287 kB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 287.3/287.3 kB 22.5 MB/s eta 0:00:00
Collecting chex<0.1.3,>=0.0.7
Downloading chex-0.1.2-py3-none-any.whl (72 kB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 72.3/72.3 kB 8.4 MB/s eta 0:00:00
Collecting jax==0.2.12
Downloading jax-0.2.12.tar.gz (590 kB)
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 590.8/590.8 kB 49.2 MB/s eta 0:00:00
Preparing metadata (setup.py) ... done
**ERROR: Could not find a version that satisfies the requirement jaxlib==0.1.68 (from mtj-softtuner) (from versions: 0.1.75, 0.1.76, 0.3.0, 0.3.2, 0.3.5, 0.3.7, 0.3.10, 0.3.14, 0.3.15, 0.3.20, 0.3.22, 0.3.24, 0.3.25, 0.4.0, 0.4.1, 0.4.2, 0.4.3, 0.4.4, 0.4.6, 0.4.7)
ERROR: No matching distribution found for jaxlib==0.1.68


ModuleNotFoundError Traceback (most recent call last)

in <cell line: 6>()
4 get_ipython().system('bash mtj-softtuner/install.sh')
5
----> 6 import mtj_softtuner
7
8 import os

ModuleNotFoundError: No module named 'mtj_softtuner'**

Issue with trainer.tokenize_dataset

When I try to use this notebook in its google colab implementation I am able to run it down to where you make the npy file. However, when I try to run that block I get the following error. Any thoughts on why, or what my problem is?


TypeError Traceback (most recent call last)
in
3 batch_size = 2048 # @param {type:"integer"}
4 epochs = 1 # @param {type:"integer"}
----> 5 trainer.tokenize_dataset(dataset_path, output_file, batch_size, epochs)
6 trainer.save_data()
7 print("OK.")

4 frames
/usr/lib/python3.7/posixpath.py in join(a, *p)
78 will be discarded. An empty last part will result in a path that
79 ends with a separator."""
---> 80 a = os.fspath(a)
81 sep = _get_sep(a)
82 path = a

TypeError: expected str, bytes or os.PathLike object, not NoneType

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.