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[AINews] Autoresearch: Sparks of Recursive Self Improvement
AGI takes another small step forward.
Accelerating LLM inference with post-training weight and activation using AWQ and GPTQ on Amazon SageMaker AI
Quantized models can be seamlessly deployed on Amazon SageMaker AI using a few lines of code. In this post, we explore why quantization matters—how it enables lower-cost inference, supports deployment on resource-constrained hardware, and reduces both the financial and environmental impact of modern LLMs, while preserving most of their original performance. We also take a deep dive into the principles behind PTQ and demonstrate how to quantize the model of your choice and deploy it on Amazon SageMaker.
[State of Code Evals] After SWE-bench, Code Clash & SOTA Coding Benchmarks recap — John Yang
From creating SWE-bench in a Princeton basement to shipping CodeClash, SWE-bench Multimodal, and SWE-bench Multilingual, John Yang has spent the last year and a half watching his benchmark become the de facto standard for evaluating AI coding agents—trusted by Cognition (Devin), OpenAI, Anthropic, and every major lab racing to solve software engineering at scale.
Venice: Uncensored (free) (cognitivecomputations/dolphin-mistral-24b-venice-edition)
Venice Uncensored Dolphin Mistral 24B Venice Edition is a fine-tuned variant of Mistral-Small-24B-Instruct-2501, developed by dphn.ai in collaboration with Venice.ai. This model is designed as an “uncensored” instruct-tuned LLM, preserving user control over alignment, system prompts, and behavior. Intended for advanced and unrestricted use cases, Venice Uncensored emphasizes steerability and transparent behavior, removing default safety and alignment layers typically found in mainstream assistant models.
Dolphin3.0 R1 Mistral 24B (cognitivecomputations/dolphin3.0-r1-mistral-24b)
Dolphin 3.0 R1 is the next generation of the Dolphin series of instruct-tuned models. Designed to be the ultimate general purpose local model, enabling coding, math, agentic, function calling, and general use cases. The R1 version has been trained for 3 epochs to reason using 800k reasoning traces from the Dolphin-R1 dataset. Dolphin aims to be a general purpose reasoning instruct model, similar to the models behind ChatGPT, Claude, Gemini. Part of the Dolphin 3.0 Collection Curated and trained by Eric Hartford , Ben Gitter , BlouseJury and DphnAI
Dolphin3.0 Mistral 24B (cognitivecomputations/dolphin3.0-mistral-24b)
Dolphin 3.0 is the next generation of the Dolphin series of instruct-tuned models. Designed to be the ultimate general purpose local model, enabling coding, math, agentic, function calling, and general use cases. Dolphin aims to be a general purpose instruct model, similar to the models behind ChatGPT, Claude, Gemini. Part of the Dolphin 3.0 Collection Curated and trained by Eric Hartford , Ben Gitter , BlouseJury and DphnAI
Dolphin Llama 3 70B 🐬 (cognitivecomputations/dolphin-llama-3-70b)
Dolphin 2.9 is designed for instruction following, conversational, and coding. This model is a fine-tune of Llama 3 70B . It demonstrates improvements in instruction, conversation, coding, and function calling abilities, when compared to the original. Uncensored and is stripped of alignment and bias, it requires an external alignment layer for ethical use. Users are cautioned to use this highly compliant model responsibly, as detailed in a blog post about uncensored models at erichartford.com/uncensored-models . Usage of this model is subject to Meta's Acceptable Use Policy .
Dolphin 2.9.2 Mixtral 8x22B 🐬 (cognitivecomputations/dolphin-mixtral-8x22b)
Dolphin 2.9 is designed for instruction following, conversational, and coding. This model is a finetune of Mixtral 8x22B Instruct . It features a 64k context length and was fine-tuned with a 16k sequence length using ChatML templates. This model is a successor to Dolphin Mixtral 8x7B . The model is uncensored and is stripped of alignment and bias. It requires an external alignment layer for ethical use. Users are cautioned to use this highly compliant model responsibly, as detailed in a blog post about uncensored models at erichartford.com/uncensored-models . #moe #uncensored
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