fickling
petals
fickling | petals | |
---|---|---|
7 | 98 | |
333 | 8,710 | |
5.1% | 1.8% | |
8.4 | 8.3 | |
3 days ago | 12 days ago | |
Python | Python | |
GNU Lesser General Public License v3.0 only | MIT License |
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fickling
- Fickling – A Python pickling decompiler and static analyzer
- ⚠️WARNING⚠️ never open a .ckpt file without knowing exactly what's inside (especially SDXL)
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Facebook LLAMA is being openly distributed via torrents
You're right! You should probably use Trail of Bits Fickling tool to investigate. https://github.com/trailofbits/fickling
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Safety of downloading random checkpoints
I tested the Anything V3 pruned from Hugging Face, and indeed nothing funny in its pickle. I used the Fickling library to decompile it. I do not use Windows so my interests in .ckpt security are largely related to Pickle exploits— which could extract malicious code from a data file and then do something with it, but the data files themselves are not executed. I will edit this comment with lines referencing that data file.
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Draw Things, Stable Diffusion in your pocket, 100% offline and free
I've been using Diffusion Bee on my Mac, and it's just gained the ability to import models (which it converts), but it is unpickling to do so— but barely. It unpickles, figures out what sort of data is in every data file and then computes what it wants from them on its own. I would love it to not use unpickling at all, so my intention is if I can figure it out, to write a script to decode the pickle file (with Fickling or otherwise) and then just do the weight calculation/assignment.
- Novel AI models allegedly leaked.
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Never a dill moment: Exploiting machine learning pickle files
Something you won't gather from skim-reading the headline is that this is that the author has also created a tool, Fickling: https://github.com/trailofbits/fickling - to aid in playing around with pickle files.
From the article: [Fickling] can help you reverse engineer, test, and even create malicious pickle files.
petals
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Mistral Large
So how long until we can do an open source Mistral Large?
We could make a start on Petals or some other open source distributed training network cluster possibly?
[0] https://petals.dev/
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Distributed Inference and Fine-Tuning of Large Language Models over the Internet
Can check out their project at https://github.com/bigscience-workshop/petals
- Make no mistake—AI is owned by Big Tech
- Would you donate computation and storage to help build an open source LLM?
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Run 70B LLM Inference on a Single 4GB GPU with This New Technique
There is already an implementation along the same line using the torrent architecture.
https://petals.dev/
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Run LLMs in bittorrent style
Check it out at Petals.dev. Chatbot
- Is distributed computing dying, or just fading into the background?
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Ask HN: Are there any projects currently exploring distributed AI training?
https://github.com/bigscience-workshop/petals
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Mistral 7B,The complete Guide of the Best 7B model
https://github.com/bigscience-workshop/petals
Inference only: https://lite.koboldai.net/
- Run LLMs at home, BitTorrent‑style
What are some alternatives?
swift-diffusion
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
diffusionbee-stable-diffusion-ui - Diffusion Bee
llama - Inference code for Llama models
safer_unpickle
alpaca-lora - Instruct-tune LLaMA on consumer hardware
sd-webui-model-converter - model convert extension for stable-diffusion-webui. supports convert fp16/bf16 no-ema/ema-only safetensors
GLM-130B - GLM-130B: An Open Bilingual Pre-Trained Model (ICLR 2023)
Auto-GPT - An experimental open-source attempt to make GPT-4 fully autonomous. [Moved to: https://github.com/Significant-Gravitas/Auto-GPT]
Open-Assistant - OpenAssistant is a chat-based assistant that understands tasks, can interact with third-party systems, and retrieve information dynamically to do so.
nanoGPT - The simplest, fastest repository for training/finetuning medium-sized GPTs.
ollama - Get up and running with Llama 3, Mistral, Gemma, and other large language models.