The following assumes you are using a AArch64 host.
Setup SDK and emulator :
# https://developer.android.com/studio/index.html#command-line-tools-only
sudo apt-get install unzip openjdk-17-jdk gradle -y| { | |
| "tools": [ | |
| { | |
| "type": "function", | |
| "function": { | |
| "name": "codebase_search", | |
| "description": "Find snippets of code from the codebase most relevant to the search query.\nThis is a semantic search tool, so the query should ask for something semantically matching what is needed.\nIf it makes sense to only search in particular directories, please specify them in the target_directories field.\nUnless there is a clear reason to use your own search query, please just reuse the user's exact query with their wording.\nTheir exact wording/phrasing can often be helpful for the semantic search query. Keeping the same exact question format can also be helpful.", | |
| "parameters": { | |
| "type": "object", | |
| "properties": { |
This worked on 14/May/23. The instructions will probably require updating in the future.
llama is a text prediction model similar to GPT-2, and the version of GPT-3 that has not been fine tuned yet. It is also possible to run fine tuned versions (like alpaca or vicuna with this. I think. Those versions are more focused on answering questions)
Note: I have been told that this does not support multiple GPUs. It can only use a single GPU.
It is possible to run LLama 13B with a 6GB graphics card now! (e.g. a RTX 2060). Thanks to the amazing work involved in llama.cpp. The latest change is CUDA/cuBLAS which allows you pick an arbitrary number of the transformer layers to be run on the GPU. This is perfect for low VRAM.
08737ef720f0510c7ec2aa84d7f70c691073c35d.| import time | |
| import frida | |
| import json | |
| enc_cipher_hashcodes = [] #cipher objects with Cipher.ENCRYPT_MODE will be stored here | |
| dec_cipher_hashcodes = [] #cipher objects with Cipher.ENCRYPT_MODE will be stored here | |
| def my_message_handler(message, payload): | |
| #mainly printing the data sent from the js code, and managing the cipher objects according to their operation mode | |
| if message["type"] == "send": |
| // Android 4.1+ | |
| dependencies { | |
| implementation 'com.squareup.okhttp3:okhttp:3.12.13' | |
| implementation 'org.conscrypt:conscrypt-android:2.5.2' | |
| } | |
| // Android 5.0+ | |
| dependencies { | |
| implementation 'com.squareup.okhttp3:okhttp:4.10.0' | |
| implementation 'org.conscrypt:conscrypt-android:2.5.2' |
| Hi All! | |
| I've recently launched a tool that wraps many of the commands here with a user interface. This desktop application is currently available for macOS. There's a roadmap outlining planned features for the near future. | |
| Feel free to request any features you'd like to see, and I'll prioritize them accordingly. | |
| One of the most important aspects of this application is that every command executed behind the scenes is displayed in a special log section. This allows you to see exactly what’s happening and learn from it. | |
| Here's the link to the repository: https://github.com/Pulimet/ADBugger | |
| App Description: | |
| ADBugger is a desktop tool designed for debugging and QA of Android devices and emulators. It simplifies testing, debugging, and performance analysis by offering device management, automated testing, log analysis, and remote control capabilities. This ensures smooth app performance across various setups. |
The idea is to provide a database as a service to end users in such a way that no one except the user herself can access the data, not even the hosting provider or the database administrator.
Other people's projects:
My projects (tutorials are on my blog at http://maxoffsky.com):