Nicolay Gerold
@nicolaygerold
Nicolay Gerold
The text embedding set trained by Jina AI, Finetuner team.
Intended Usage & Model Info
jina-embeddings-v2-base-en is an English, monolingual embedding model supporting 8192 sequence length.
It is based on a Bert architecture (JinaBert) that supports the symmetric bidirectional variant of ALiBi to allow longer sequence length.
The backbone... See more
Intended Usage & Model Info
jina-embeddings-v2-base-en is an English, monolingual embedding model supporting 8192 sequence length.
It is based on a Bert architecture (JinaBert) that supports the symmetric bidirectional variant of ALiBi to allow longer sequence length.
The backbone... See more
jinaai/jina-embeddings-v2-base-en · Hugging Face
Unitxt is a python library for getting data fired up and set for utilization. In one line of code, it preps a dataset or mixtures-of-datasets into an input-output format for training and evaluation. We aspire to be simple, adaptable and transparent.
Unitxt builds on separation. Separation allows adding a dataset, without knowing anything about the... See more
Unitxt builds on separation. Separation allows adding a dataset, without knowing anything about the... See more
IBM • GitHub - IBM/unitxt: 🦄 Unitxt: a python library for getting data fired up and set for training and evaluation
LLM Training and Tools
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.
multimodal-maestro
👋 hello
Multimodal-Maestro gives you more control over large multimodal models to get the outputs you want. With more effective prompting tactics, you can get multimodal models to do tasks you didn't know (or think!) were possible. Curious how it works? Try our HF space!
👋 hello
Multimodal-Maestro gives you more control over large multimodal models to get the outputs you want. With more effective prompting tactics, you can get multimodal models to do tasks you didn't know (or think!) were possible. Curious how it works? Try our HF space!
roboflow • GitHub - roboflow/multimodal-maestro: Effective prompting for Large Multimodal Models like GPT-4 Vision, LLaVA or CogVLM. 🔥
Certain artificial sweeteners disrupt the microbiome and favor the environment for unfavorable
Andrew Huberman • How Foods and Nutrients Control Our Moods
Dr. Charles Zuker: The Biology of Taste Perception & Sugar Craving
hubermanlab.com
When it comes to identifying where generative AI can make an impact, we dig into challenges that commonly:
- Involve analysis, interpretation, or review of unstructured content (e.g. text) at scale
- Require massive scaling that may be otherwise prohibitive due to limited resources
- Would be challenging for rules-based or traditional ML approaches
Developing Rapidly with Generative AI
Towhee is a cutting-edge framework designed to streamline the processing of unstructured data through the use of Large Language Model (LLM) based pipeline orchestration. It is uniquely positioned to extract invaluable insights from diverse unstructured data types, including lengthy text, images, audio and video files. Leveraging the capabilities of... See more
towhee-io • GitHub - towhee-io/towhee: Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
Some techniques I have seen in the wild
this style was popular back in the early days of gpt-3.5 when it landed, for some reason, it fell out of fashion
Best example of this is the... See more
- Create a semi-strict programming language like promptlang - https://github.com/ruvnet/promptlang
this style was popular back in the early days of gpt-3.5 when it landed, for some reason, it fell out of fashion
- Write a super long persona mapping prompt with a well defined action space
Best example of this is the... See more