LLM Tool Use - GPT4o-mini, Groq & Llama.cpp

➡️ Get Life-time Access to the ADVANCED-inference Repo (incl. notebooks in this vid.): https://trelis.com/ADVANCED-inference/
➡️ Trelis Runpod Affiliate Link (supports the channel): https://runpod.io?ref=jmfkcdio
➡️ One-click GPU templates: https://github.com/TrelisResearch/one-click-llms

VIDEO RESOURCES:
- Slides: https://docs.google.com/presentation/d/1_aYqoGhI1yv9GdOM5lAgq3kQQnSk70mLkQkbVoPlE20/edit?usp=sharing
- llama.cpp repo: https://github.com/ggerganov/llama.cpp/blob/master/docs/build.md
- groq api: https://console.groq.com/docs/api-reference
- openai api: https://platform.openai.com/docs/models/gpt-4o-mini
- Phi-3 Mini 128k: https://huggingface.co/microsoft/Phi-3-mini-128k-instruct
- Phi-3 Mini 4-bit GGUF: https://huggingface.co/microsoft/Phi-3-mini-4k-instruct-gguf

OTHER TRELIS LINKS:
➡️ Trelis Newsletter: https://blog.Trelis.com
➡️ Trelis Resources and Support: https://Trelis.com/About

TIMESTAMPS:
0:00 Function Calling - Cheap, Fast, Local and Enterprise
0:58 Video Overview
2:48 Tool Use Flow Chart
10:18 Function preparation tips
13:08 Resources (trelis.com/ADVANCED-inference)
14:36 Code walk-through for function / tool preparation
23:50 Prompt preparation and Recursive tool use
34:58 GPT4o-mini tool use performance
37:29 Zero shot prompting and Runpod Phi-3 endpoint setup
49:34 Phi-3 Mini Zero Shot Performance
53:20 Parallel function calling with Phi-3
59:43 Low latency tool use with Groq - Zero shot
1:01:29 Groq Llama 3 8B Zero Shot Tool Use Performance
1:03:11 Groq Llama 3 8B Fine-tune Performance
1:05:42 Groq Llama 3 70B Fine-tune Performance
1:06:50 Local Phi-3 Inference on a Mac with llama.cpp
1:17:26 Final Tool Use Tips
1:19:00 Resources

Тэги:

#tool_use #tool_use_tutorial #tool_use_for_beginners #function_calling_tutorial #function_calling_groq #tool_use_groq #tool_use_gpt4o #tool_use_gpt4o-mini #function_calling_gpt4o-mini #tool_use_llamacpp #tool_use_llama.cpp #function_calling_llama.cpp #runpod_tool_use #zero_shot_function_calling #parallel_function_calling

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