All tags
Model: "phi-2"
AI gets Memory
miqumaid-v2-70b mixtral-8x7b-qlora mistral-7b phi-2 medalpaca aya openai langchain thebloke cohere unsloth-ai mistral-ai microsoft rag memory-modeling context-windows open-source finetuning sequential-fine-tuning direct-preference-optimization rlhf ppo javascript-python-integration hardware-optimization gpu-overclocking quantization model-training large-context multilinguality joanne-jang
AI Discords analysis covered 20 guilds, 312 channels, and 6901 messages. The report highlights the divergence of RAG style operations for context and memory, with implementations like MemGPT rolling out in ChatGPT and LangChain. The TheBloke Discord discussed open-source large language models such as the Large World Model with contexts up to 1 million tokens, and the Cohere aya model supporting 101 languages. Roleplay-focused models like MiquMaid-v2-70B were noted for performance improvements with enhanced hardware. Finetuning techniques like Sequential Fine-Tuning (SFT) and Direct Preference Optimization (DPO) were explained, with tools like Unsloth AI's apply_chat_template preferred over Alpaca. Integration of JavaScript and Python via JSPyBridge in the SillyTavern project was also discussed. Training challenges with Mixtral 8x7b qlora versus Mistral 7b were noted. The LM Studio Discord focused on hardware limitations affecting large model loading, medical LLMs like medAlpaca, and hardware discussions around GPU upgrades and overclocking. Anticipation for IQ3_XSS 1.5 bit quantization support in LM Studio was expressed.
12/13/2023 SOLAR10.7B upstages Mistral7B?
solar-10.7b llama-2 mistral-7b phi-2 gpt-4 gemini upstage nous-research openai mistral-ai microsoft depth-up-scaling pretraining synthetic-data gpu-training api-usage model-integration agi asi chat-models vision model-performance fine-tuning
Upstage released the SOLAR-10.7B model, which uses a novel Depth Up-Scaling technique built on the llama-2 architecture and integrates mistral-7b weights, followed by continued pre-training. The Nous community finds it promising but not exceptional. Additionally, weights for the phi-2 base model were released, trained on 1.4 trillion tokens including synthetic texts created by GPT-3 and filtered by GPT-4, using 96 A100 GPUs over 14 days. On OpenAI's Discord, users discussed challenges with various GPT models, including incoherent outputs, API usage limitations, and issues with GPT-4 Vision API. Conversations also covered understanding AGI and ASI, concerns about OpenAI's partnership with Axel Springer, and pricing changes for GPT Plus. Discussions included the Gemini chat model integrated into Bard and comparisons with GPT-4 performance.
12/12/2023: Towards LangChain 0.1
mixtral-8x7b phi-2 gpt-3 chatgpt gpt-4 langchain mistral-ai anthropic openai microsoft mixture-of-experts information-leakage prompt-engineering oauth2 logo-generation education-ai gaming-ai api-access model-maintainability scalability
The Langchain rearchitecture has been completed, splitting the repo for better maintainability and scalability, while remaining backwards compatible. Mistral launched a new Discord community, and Anthropic is rumored to be raising another $3 billion. On the OpenAI Discord, discussions covered information leakage in AI training, mixture of experts (MoE) models like mixtral 8x7b, advanced prompt engineering techniques, and issues with ChatGPT performance and API access. Users also explored AI applications in logo generation, education, and gaming, and shared solutions for Oauth2 authentication problems. A new small language model named Phi-2 was mentioned from Microsoft.