KoboldAI
Pytorch
Our great sponsors
KoboldAI | Pytorch | |
---|---|---|
41 | 338 | |
327 | 78,016 | |
- | 2.7% | |
9.5 | 10.0 | |
14 days ago | about 7 hours ago | |
C++ | Python | |
GNU Affero General Public License v3.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
KoboldAI
-
LLM spews nonsense in CVE report for curl
It’s not that big a task as all that. There are a lot of unaligned models available, and user interfaces that aren’t that hard to use.
https://github.com/henk717/KoboldAI
-
Chat with, and help host, a free community LLM "horde"
https://github.com/henk717/KoboldAI
- Hosts pick a quantized community LLM to run, which is (IMO) the real magic of this system. Cloud services tend to run generic Llama chat/instruct models, OpenAI API models, or maybe a single proprietary finetune, but the Llama/Mistral finetuning community is red hot. New finetines and crazy merges/hybrids that outperform llama-chat in specific tasks (mostly Chat/Story/RP) come out every day, and each one has a different "flavor" and format:
https://huggingface.co/models?sort=modified&search=mistral+g...
- Run LLMs with KoboldaAI on Intel ARC
-
No idea what I'm doing help
Sourceforge is our official version but that one is to old to run newer models like Holomax, the releases for United can be found here : https://github.com/henk717/KoboldAI/releases
-
Still getting "read only" on JanitorAI even after setting model. Do I need to change anything config wise to get it to use pygmalion?
Colab Check: False, TPU: False INIT | OK | KAI Horde Models INFO | __main__::648 - We loaded the following model backends: KoboldAI API KoboldAI Old Colab Method Huggingface GooseAI Horde OpenAI Read Only INFO | __main__:general_startup:1363 - Running on Repo: https://github.com/henk717/koboldai Branch: INIT | Starting | Flask INIT | OK | Flask INIT | Starting | Webserver INIT | OK | Webserver MESSAGE | Webserver started! You may now connect with a browser at http://127.0.0.1:8501 INIT | Searching | GPU support INIT | Found | GPU support INIT | Starting | LUA bridge INIT | OK | LUA bridge INIT | Starting | LUA Scripts INIT | OK | LUA Scripts Setting Seed Traceback (most recent call last): File "B:\python\lib\site-packages\eventlet\hubs\selects.py", line 59, in wait listeners.get(fileno, hub.noop).cb(fileno) File "B:\python\lib\site-packages\eventlet\greenthread.py", line 221, in main result = function(*args, **kwargs) File "B:\python\lib\site-packages\eventlet\wsgi.py", line 837, in process_request proto.__init__(conn_state, self) File "B:\python\lib\site-packages\eventlet\wsgi.py", line 352, in __init__ self.finish() File "B:\python\lib\site-packages\eventlet\wsgi.py", line 751, in finish BaseHTTPServer.BaseHTTPRequestHandler.finish(self) File "B:\python\lib\socketserver.py", line 811, in finish self.wfile.close() File "B:\python\lib\socket.py", line 687, in write return self._sock.send(b) File "B:\python\lib\site-packages\eventlet\greenio\base.py", line 401, in send return self._send_loop(self.fd.send, data, flags) File "B:\python\lib\site-packages\eventlet\greenio\base.py", line 388, in _send_loop return send_method(data, *args) ConnectionAbortedError: [WinError 10053] An established connection was aborted by the software in your host machine Removing descriptor: 1488 Connection Attempt: 127.0.0.1 INFO | __main__:do_connect:2574 - Client connected! UI_1 TODO: Allow config INFO | modeling.inference_models.hf:set_input_parameters:189 - {'0_Layers': 18, 'CPU_Layers': 10, 'Disk_Layers': 0, 'class': 'model', 'label': 'PygmalionAI_pygmalion-6b', 'id': 'PygmalionAI_pygmalion-6b', 'name': 'PygmalionAI_pygmalion-6b', 'size': '', 'menu': 'Custom', 'path': 'C:\\KoboldAI\\models\\PygmalionAI_pygmalion-6b', 'ismenu': 'false', 'plugin': 'Huggingface'} INIT | Searching | GPU support INIT | Found | GPU support Loading checkpoint shards: 100%|█████████████████████████████████████████████████████████| 2/2 [00:19<00:00, 9.60s/it] Loading model tensors: 100%|##########| 56/56 [00:05<00:00, 9.52it/s]INIT | Starting | LUA bridge0, 8.93s/it] INIT | OK | LUA bridge INIT | Starting | LUA Scripts INIT | OK | LUA Scripts Setting Seed Connection Attempt: 127.0.0.1 INFO | __main__:do_connect:2574 - Client connected! UI_1
-
Kobold API URL for Chub Venus Ai
That is our developer version, its selectable in the Colab version dropdown and also available on https://github.com/henk717/koboldai
-
I got KoboldAI running on my computer and successfully connected it to Janitor, heres a small tutorial
Download Kobold from THIS LINK:https://github.com/henk717/KoboldAI. I downloaded Kobold from a different Github link and it wouldnt work, you need to get this specific one. Click on "code", then download zip
-
I created a repo on Github to categorize AI models. You can browse AIs from many categories!
https://github.com/henk717/KoboldAI https://github.com/LostRuins/koboldcpp/ https://github.com/ggerganov/llama.cpp https://github.com/AUTOMATIC1111/stable-diffusion-webui https://github.com/oobabooga/text-generation-webui
-
Meta’s new AI lets people make chatbots. They’re using it for sex.
For the third, I don't think Oobabooga supports the horde but KoboldAI does. I won't go into how to install KoboldAI since Oobabooga should give you enough freedom with 7B, 13B and maybe 30B models (depending on available RAM), but KoboldAI lets you download some models directly from the web interface, supports using online service providers to run the models for you, and supports the horde with a list of available models to choose from.
-
Kobold AI broke after update (New to this)
"Your Pytorch installation did not update correctly, you can solve this by running install_requirements.bat in the mode where it deletes the existing runtime. Alternative you can download a fresh copy of the offline installer for KoboldAI United from : https://github.com/henk717/KoboldAI/releases"
Pytorch
-
Einsum in 40 Lines of Python
PyTorch also has some support for them, but it's quite incomplete and has many issues so that it is basically unusable. And its future development is also unclear. https://github.com/pytorch/pytorch/issues/60832
-
Library for Machine learning and quantum computing
TensorFlow
-
My Favorite DevTools to Build AI/ML Applications!
TensorFlow, developed by Google, and PyTorch, developed by Facebook, are two of the most popular frameworks for building and training complex machine learning models. TensorFlow is known for its flexibility and robust scalability, making it suitable for both research prototypes and production deployments. PyTorch is praised for its ease of use, simplicity, and dynamic computational graph that allows for more intuitive coding of complex AI models. Both frameworks support a wide range of AI models, from simple linear regression to complex deep neural networks.
-
penzai: JAX research toolkit for building, editing, and visualizing neural nets
> does PyTorch have a similar concept
of course https://github.com/pytorch/pytorch/blob/main/torch/utils/_py...
-
Tinygrad: Hacked 4090 driver to enable P2P
fyi should work on most 40xx[1]
[1] https://github.com/pytorch/pytorch/issues/119638#issuecommen...
-
The Elements of Differentiable Programming
Sure, right here: https://github.com/pytorch/pytorch/blob/main/torch/autograd/...
Here's the documentation: https://pytorch.org/tutorials/intermediate/forward_ad_usage....
> When an input, which we call “primal”, is associated with a “direction” tensor, which we call “tangent”, the resultant new tensor object is called a “dual tensor” for its connection to dual numbers[0].
-
Functions and operators for Dot and Matrix multiplication and Element-wise calculation in PyTorch
*My post explains Dot, Matrix and Element-wise multiplication in PyTorch.
-
Dot vs Matrix vs Element-wise multiplication in PyTorch
In PyTorch with @, dot() or matmul():
-
Building a GPT Model from the Ground Up!
import torch # we use PyTorch: https://pytorch.org data = torch.tensor(encode(text), dtype=torch.long) print(data.shape, data.dtype) print(data[:1000]) # the 1000 characters we looked at earlier will to the GPT look like this
-
Open Source Ascendant: The Transformation of Software Development in 2024
AI's Open Embrace Artificial intelligence (AI) and machine learning (ML) are increasingly leveraging open-source frameworks like TensorFlow [https://www.tensorflow.org/] and PyTorch [https://pytorch.org/]. This democratization of AI tools is driving innovation and lowering entry barriers across industries.
What are some alternatives?
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
KoboldAI-Client
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
koboldcpp - A simple one-file way to run various GGML and GGUF models with KoboldAI's UI
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing
KoboldAI
flax - Flax is a neural network library for JAX that is designed for flexibility.
stable-diffusion-webui - Stable Diffusion web UI
tinygrad - You like pytorch? You like micrograd? You love tinygrad! ❤️ [Moved to: https://github.com/tinygrad/tinygrad]
llama.cpp - LLM inference in C/C++
Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more