GitHub - promptslab/LLMtuner: Tune LLM in few lines of code
slowllama
Fine-tune Llama2 and CodeLLama models, including 70B/35B on Apple M1/M2 devices (for example, Macbook Air or Mac Mini) or consumer nVidia GPUs.
slowllama is not using any quantization. Instead, it offloads parts of model to SSD or main memory on both forward/backward passes. In contrast with training large models from scratch (unattainable... See more
Fine-tune Llama2 and CodeLLama models, including 70B/35B on Apple M1/M2 devices (for example, Macbook Air or Mac Mini) or consumer nVidia GPUs.
slowllama is not using any quantization. Instead, it offloads parts of model to SSD or main memory on both forward/backward passes. In contrast with training large models from scratch (unattainable... See more
okuvshynov • GitHub - okuvshynov/slowllama: Finetune llama2-70b and codellama on MacBook Air without quantization
Nicolay Gerold added
TL;DR
LLMLingua utilizes a compact, well-trained language model (e.g., GPT2-small, LLaMA-7B) to identify and remove non-essential tokens in prompts. This approach enables efficient inference with large language models (LLMs), achieving up to 20x compression with minimal performance loss.
... See more
LLMLingua utilizes a compact, well-trained language model (e.g., GPT2-small, LLaMA-7B) to identify and remove non-essential tokens in prompts. This approach enables efficient inference with large language models (LLMs), achieving up to 20x compression with minimal performance loss.
... See more
microsoft • GitHub - microsoft/LLMLingua: To speed up LLMs' inference and enhance LLM's perceive of key information, compress the prompt and KV-Cache, which achieves up to 20x compression with minimal performance loss.
Nicolay Gerold added
Ollama
ollama.comStamati and added
🌳 Galileo LLM Studio
Algorithm-powered LLMOps Platform
Find the best prompt, inspect data errors while fine-tuning, monitor LLM outputs in real-time. All in one powerful, collaborative platform.
Testing framework for LLM Part
Nicolay Gerold added
Welcome to prompttools created by Hegel AI! This repo offers a set of open-source, self-hostable tools for experimenting with, testing, and evaluating LLMs, vector databases, and prompts. The core idea is to enable developers to evaluate using familiar interfaces like code, notebooks, and a local playground.... See more
In just a few lines of codes, you can t
Testing framework for LLM Part
Nicolay Gerold added
GitHub - mit-han-lab/streaming-llm: Efficient Streaming Language Models with Attention Sinks
mit-han-labgithub.comDarren LI and added
GitHub - arthur-ai/bench: A tool for evaluating LLMs
GitHub - arthur-ai/bench: A tool for evaluating LLMs
BA Builder added
Clean & curate your data with LLMs
databonsai is a Python library that uses LLMs to perform data cleaning tasks.
Features
databonsai is a Python library that uses LLMs to perform data cleaning tasks.
Features
- Suite of tools for data processing using LLMs including categorization, transformation, and extraction
- Validation of LLM outputs
- Batch processing for token savings
- Retry logic with exponential backoff for handling rate limits an
databonsai • GitHub - databonsai/databonsai: clean & curate your data with LLMs.
Nicolay Gerold added