LLMs
.png?table=block&id=e222d02f-1d78-4887-8972-a958b1fbca65&spaceId=996f2b3b-deaa-4214-aedb-cbc914a1833e&width=1250&userId=&cache=v2)
Jail-Breaked & Offline Appliances: It’s becoming increasingly clear that we’ll be able to interact with everyday appliances and devices with natural language. As locally run LLMs become more efficient and powerful, the prospects of having a conversation with your coffee machine in the morning aren’t unreasonable. After all, who wants to tinker with... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
The exact metrics we use depend on the application — our main goal is to understand how users use the feature and quickly make improvements to better meet their needs. For internal applications, this might mean measuring efficiency and sentiment. For consumer-facing applications, we similarly focus on measures of user satisfaction - direct user... See more
Developing Rapidly with Generative AI
Developers can now generate human-quality speech from text via the text-to-speech API. Our new TTS model offers six preset voices to choose from and two model variants, tts-1 and tts-1-hd . tts is optimized for real-time use cases and tts-1-hd is optimized for quality. Pricing starts at $0.015 per input 1,000 characters. Check out our TTS guide to... See more
New models and developer products announced at DevDay
Today, we’re releasing the Assistants API, our first step towards helping developers build agent-like experiences within their own applications. An assistant is a purpose-built AI that has specific instructions, leverages extra knowledge, and can call models and tools to perform tasks. The new Assistants API provides new capabilities such as Code... See more
New models and developer products announced at DevDay
One thing that is still confusing to me, is that we've been building products with machine learning pretty heavily for a decade now and somehow abandoned all that we have learned about the process now that we're building "AI".
The biggest thing any ML practitioner realizes when they step out of a research setting is that for most tasks accuracy has... See more
The biggest thing any ML practitioner realizes when they step out of a research setting is that for most tasks accuracy has... See more
Ask HN: What are some actual use cases of AI Agents right now? | Hacker News
You are assuming that the probability of failure is independent, which couldn't be further from the truth. If a digit recogniser can recognise one of your "hard" handwritten digits, such as a 4 or a 9, it will likely be able to recognise all of them.
The same happens with AI agents. They are not good at some tasks, but really really food at others.
LLMTuner
LLMTuner: Fine-Tune Llama, Whisper, and other LLMs with best practices like LoRA, QLoRA, through a sleek, scikit-learn-inspired interface.
LLMTuner: Fine-Tune Llama, Whisper, and other LLMs with best practices like LoRA, QLoRA, through a sleek, scikit-learn-inspired interface.
promptslab • GitHub - promptslab/LLMtuner: Tune LLM in few lines of code
How can we make interacting with conversational models feel more natural?
Every conversational interface to a language model adopts the same pattern:
A chat history sidebar, with each conversation lasting just a few turns
New sessions always begin in a brand-new thread
Every user query must always elicit exactly one response
None of these assumptions... See more
Every conversational interface to a language model adopts the same pattern:
A chat history sidebar, with each conversation lasting just a few turns
New sessions always begin in a brand-new thread
Every user query must always elicit exactly one response
None of these assumptions... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
𝘱𝘦𝘳𝘧𝘰𝘳𝘮𝘢𝘯𝘤𝘦: it will improve your LLM performance on given use cases (e.g., coding, extracting text, etc.). Mainly, the LLM will specialize in a given task (a specialist will always beat a generalist in its domain)
𝘤𝘰𝘯𝘵𝘳𝘰𝘭: you can refine how your model should behave on specific inputs and outputs, resulting in a more robust product
𝘮𝘰𝘥𝘶𝘭𝘢𝘳𝘪𝘻𝘢𝘵𝘪𝘰𝘯:... See more
𝘤𝘰𝘯𝘵𝘳𝘰𝘭: you can refine how your model should behave on specific inputs and outputs, resulting in a more robust product
𝘮𝘰𝘥𝘶𝘭𝘢𝘳𝘪𝘻𝘢𝘵𝘪𝘰𝘯:... See more
Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
Motivation for finetuning