FAST Local Live LLM Preview Window - Phi-2 / Mistral 7B Uncensored
Ғылым және технология
FAST Local Live LLM Preview Window - Phi-2 / Mistral 7B Uncensored
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In this video i create a project where we get a real time live preview of the llm output, running on local models like uncensored Phi-2 and Mistral 7B. Very fun and simple project.
00:00 Local Live LLM Preview Window Intro
00:20 Flowchart
01:32 Python Code
04:01 Live LLM Preview Test 1
04:57 Live LLM Preview Test 2
05:22 Live LLM Preview Test 3
Пікірлер: 23
I think that should officially replace "Hello World" from now on. 😆👍
😂 the first email was hilarious!!
Beautiful
Graet - thank you:)
I've had great results with the beagle models! Even the 3 bit version does better than some of the big models for things like evaluating RAG results.
hiliarious concept
🎯 Key Takeaways for quick navigation: 00:27 🐍 *Developed a local real-time LLM (Language Model) preview using Python and threading.* 01:23 🔄 *Parallel function allows capturing and processing keyboard inputs without interruption.* 01:49 📝 *Python code includes M7B function for local LM Studio, update preview function, and capture input function.* 03:27 🗣️ *System prompts for the Mistral 7B model include examples for a 4chan Reddit style and a more explicit chatbot style.* 04:09 🖥️ *Demonstrates the local real-time preview in action with user input and model responses.* 05:32 🔄 *Switches the model to Open Hermis Mistral 7P, adjusts settings, and changes the system prompt for a different tone.* 06:28 📧 *Tests the modified model by writing a short, humorous, and explicit email using keyboard input.* 08:31 💻 *Encourages support through channel membership for access to scripts and the community GitHub and Discord.*
How does it feel to be a demigod? Thank you for sharing your spells!
Great content. I'm LMFAO.
really love the web troll lol
Can we do a real-time llm that works with ollama STT then Ollama then TTS in the terminal. Ollama is the most optimized llm solution.
@goodchoice4410
3 ай бұрын
check out twinny
@Canna_Science_and_Technology
3 ай бұрын
Just use the ollama end point. All done
@Edward_ZS
3 ай бұрын
@Canna_Science_and_Technology with ollama, don't you need additional headers? For model and pre-prompt
@Edward_ZS
3 ай бұрын
@Canna_Science_and_Technology curl localhost:11434/api/generate -d '{ "model": "tinydolphin", "prompt": "As a friendly and informative assistant, provide detailed explanations. This is a test. Output:", "options": { "stop": ["Instruct:", "Output:"] }, "raw": true, "stream": true }'
@Canna_Science_and_Technology
3 ай бұрын
@@Edward_ZS yes, host.docker.internal:11434/api
Where do I find dolphin phi 2 q5 k m
you obviously need a debounce on that input
I feel like this would have been much better in streamlit