tuning_playbook
gpt_index
| tuning_playbook | gpt_index | |
|---|---|---|
| 16 | 48 | |
| 25,414 | 7,332 | |
| 2.6% | - | |
| 4.7 | 9.8 | |
| about 1 month ago | about 1 year ago | |
| Python | ||
| GNU General Public License v3.0 or later | MIT License |
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tuning_playbook
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When Random Numbers Are Too Random: Low Discrepancy Sequences
These are also called quasirandom numbers. Despite games, another use case is for hyperparameter search for neural networks.
https://github.com/google-research/tuning_playbook?tab=readm...
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Hyperparameter Optimization for LLMs via Scaling Laws
[2] https://github.com/google-research/tuning_playbook
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Beyond Automatic Differentiation
Batch size can be used for regularisation, but using it for that will limit training performance. From the Google Research Tuning Playbook:
> The batch size governs the training speed and shouldn't be used to directly tune the validation set performance. Often, the ideal batch size will be the largest batch size supported by the available hardware.
> […]
> As long as all hyperparameters are well-tuned (especially the learning rate and regularization hyperparameters) and the number of training steps is sufficient, the same final performance should be attainable using any batch size (see Shallue et al. 2018).
https://github.com/google-research/tuning_playbook#choosing-...
The ideal case is full-batch with tuneable regularisation, just the hardware gets expensive.
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Modeling methodology
Regarding tuning params, this is an excellent read: https://github.com/google-research/tuning_playbook
- About the hardware
- I asked an AI to create an Asmongold story and then had another AI generate voice. There it is dude
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Trending ML repos of the week 📈
3️⃣ google-research/tuning_playbook
- AI全靠偷欧美开源的
- Deep learning tuning playbook
gpt_index
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Basic links to get started with Prompt Programming
LLAMA Index Github repository
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Leak: Metas GPT-Herausforderer LLaMA als Torrent verfügbar
Zuwendungen kommen auch so langsam ( LLamaIndex ) https://github.com/jerryjliu/gpt_index
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Large language models are having their Stable Diffusion moment
This is exactly what LlamaIndex is meant to solve!
A set of data structures to augment LLM's with your data: https://github.com/jerryjliu/gpt_index
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ChatGPT's API Is So Good and Cheap, It Makes Most Text Generating AI Obsolete
This is what we've designed LlamaIndex for! https://github.com/jerryjliu/gpt_index. Designed to help you "index" over a large doc corpus in different ways for use with LLM prompts.
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Is there a way I can have ChatGPT look at a document of mine?
https://github.com/jerryjliu/gpt_index might be close to what you need.
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AI is making it easier to create more noise, when all I want is good search
I would start with https://gpt-index.readthedocs.io/en/latest/ and https://langchain.readthedocs.io/en/latest/
- GitHub - jerryjliu/gpt_index: LlamaIndex (GPT Index) is a project that provides a central interface to connect your LLM's with external data.
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Using OpenAI with self hosted knowledge database
People have been doing this with https://github.com/jerryjliu/gpt_index
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Long form content
Here is a link to the repository. Take a look at the overview section of the readme. https://github.com/jerryjliu/gpt_index
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LLaMA: A foundational, 65B-parameter large language model
(creator of gpt index / llamaindex here https://github.com/jerryjliu/gpt_index)
Funny that we had just rebranded our tool from GPT Index to LlamaIndex about a week ago to avoid potential trademark issues with OpenAI, and turns out Meta has similar ideas around LLM+llama puns :). Must mean the name is good though!
Also very excited to try plugging in the LLaMa model into LlamaIndex, will report the results.
What are some alternatives?
dadaptation - D-Adaptation for SGD, Adam and AdaGrad
langchain - ⚡ Building applications with LLMs through composability ⚡ [Moved to: https://github.com/langchain-ai/langchain]
arb - Arb has been merged into FLINT -- use https://github.com/flintlib/flint/ instead
llama - Inference code for Llama models
nn-zero-to-hero - Neural Networks: Zero to Hero
awesome-chatgpt-prompts - This repo includes ChatGPT prompt curation to use ChatGPT better.
ML-Papers-Explained - Explanation to key concepts in ML
text-generation-webui - A Gradio web UI for Large Language Models. Supports transformers, GPTQ, AWQ, EXL2, llama.cpp (GGUF), Llama models.
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.
finetuner - :dart: Task-oriented embedding tuning for BERT, CLIP, etc.