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243 件
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スライド 4 枚7:21EN
Matthew Berman· 2023年6月26日Testing Orca Mini 13B, an Unofficial Model Inspired by OrcaMatthew Berman · Forward FutureMatthew Berman loads a quantized Orca Mini 13B and tries coding, reasoning, arithmetic, and summarization prompts. His 2023 informal test produces several failures and a few successes.Open-weight models評価(Evals)Distillation+2
スライド 4 枚13:50EN
Matthew Berman· 2023年6月23日MPT-30B: Running MosaicML’s Model Locally and Testing Its Chat VariantMatthew Berman · Forward FutureMatthew Berman reviews MosaicML’s June 2023 release, demonstrates a local setup, and puts the hosted chat model through an informal prompt rubric.Open-weight modelsLocal inferenceQuantization+2
スライド 3 枚8:17EN
Matthew Berman· 2023年6月22日Using OpenLLM to Serve Open Models Through an APIMatthew Berman · Forward FutureMatthew Berman demonstrates a local model server, its interactive API and a Python client in a 2023 walkthrough.Open-weight modelsInferenceインフラとデプロイ+1
スライド 7 枚4:36EN
Matthew Berman· 2023年6月20日Testing WizardCoder 15B as a Local Coding AssistantMatthew Berman · Forward FutureMatthew Berman runs the 2023 WizardCoder model locally, testing small Python exercises and a longer Snake game.モデルと学習Local inferenceSoftware engineering+2
スライド 5 枚9:46EN
Matthew Berman· 2023年6月19日Installing Text Generation WebUI on Windows: A 2023 Local-Model WalkthroughMatthew Berman · Forward FutureMatthew Berman installs an early version of Text Generation WebUI, resolves setup errors and explains model downloads and interface settings. The steps and packages are historical; consult the project’s current documentation for a modern installation.Local inferenceOpen-weight modelsインフラとデプロイ+1
59:28EN
Cognitive Revolution "How AI Changes Everything"· 2023年6月16日ポッドキャストFrom $500,000 to $50,000: MosaicML Made Training Your Own Model a Priced Productホスト Nathan LabenzJonathan Frankle and Abhi Venigalla explain who is training custom LLMs, why extraction beats chat, and how ALiBi stretches a 65k context window.モデルと学習ファインチューニングPretraining & midtraining+3
スライド 4 枚10:23EN
Matthew Berman· 2023年6月15日Testing Hosted Falcon 40B and Document Chat in h2oGPTMatthew Berman · Forward FutureMatthew Berman tries H2O.ai’s 2023 hosted Falcon 40B interface on coding, writing and reasoning prompts, then demonstrates document chat.Open-weight models評価(Evals)AI research+1
スライド 5 枚19:38EN
Matthew Berman· 2023年6月9日Orca: Teaching a Smaller Model with GPT-4 ExplanationsMatthew Berman · Forward FutureMatthew Berman reviews Microsoft Research’s 2023 Orca paper and its approach to training a 13-billion-parameter model on detailed teacher responses.DistillationファインチューニングSynthetic data+2
2:41:58EN
Lex Fridman· 2023年6月8日ポッドキャスト · 2 人Zuckerberg showed up as Mark Elliott — then argued for many AIs, not oneゲスト Mark Zuckerberg · ホスト Lex FridmanOn his second Lex Fridman podcast, the Meta CEO treats a disguised first jiu-jitsu tournament, an open research model called LLaMA, and a future of many agents as the same bet: ship before it is perfect, and do not build a single god model.企業と戦略Open-source ecosystemsOpen-weight models+3
スライド 2 枚10:40EN
Matthew Berman· 2023年6月7日Testing Nous Hermes 13B Locally: Mixed Reasoning and Unsafe ResponsesMatthew Berman · Forward FutureMatthew Berman compares a 2023 quantized model on hosted and local hardware, with uneven results across coding, logic and safety.Open-weight modelsLocal inferenceBenchmarks+1
スライド 3 枚8:51EN
Matthew Berman· 2023年6月2日Falcon 40B: A 2023 Leaderboard Result and a Slow GPU TestMatthew Berman · Forward FutureMatthew Berman tries a quantized Falcon 40B Instruct checkpoint on a hosted GPU and finds useful output but slow generation.Open-weight modelsFoundation ModelsLocal inference+1
スライド 4 枚11:42EN
Matthew Berman· 2023年5月31日Guanaco and QLoRA: A 2023 Fine-Tuning and Model TestMatthew Berman · Forward FutureMatthew Berman reviews the QLoRA paper, explains the reported memory savings and tries Guanaco 65B on an informal prompt set.ファインチューニングQuantizationOpen-weight models+1
スライド 2 枚7:51EN
Matthew Berman· 2023年5月30日Running Guanaco 65B on a Cloud GPU with Runpod and Text Generation Web UIMatthew Berman · Forward FutureMatthew Berman demonstrates a 2023 workflow for renting a GPU, loading a quantized model and generating text. Model requirements, pricing and interfaces depend on the chosen version.Local inferenceインフラとデプロイOpen-weight models+2
1:20:49EN
Cognitive Revolution "How AI Changes Everything"· 2023年5月25日ポッドキャストA Wafer-Scale Chip So AI Stops Waiting on Amdahlホスト Nathan LabenzAndrew Feldman, CEO of Cerebras, tells Nathan Labenz why one 2.5-trillion-transistor die, sparse linear algebra, and a 16-machine supercomputer are a better shape than a GPU cluster.インフラとデプロイInferenceAI cost & performance+3
1:11:11EN
20VC with Harry Stebbings· 2023年5月17日ポッドキャスト · 2 人Emad Mostaque on Open AI Models, National Data and the Race to Deployゲスト Emad Mostaque · ホスト Harry StebbingsThe Stability AI co-founder describes his 2023 vision for open models, healthcare applications and AI businesses, alongside concerns about a speculative boom.Foundation ModelsOpen-weight modelsAI in healthcare+2
スライド 4 枚11:07EN
Matthew Berman· 2023年5月16日Testing MosaicML MPT-7B Chat and StoryWriter in 2023Matthew Berman · Forward FutureMatthew Berman examines MPT-7B model variants, their licenses and a mixed set of local tests.Open-weight modelsBenchmarksモデルと学習+1
1:06:02EN
20VC with Harry Stebbings· 2023年5月15日ポッドキャスト · 2 人Yann LeCun on Open AI Models, Safety and the Future of Researchゲスト Yann Lecun · ホスト Harry StebbingsMeta’s chief AI scientist discusses language models, research priorities and his contested views on AI risk and employment.AI researchAI SafetyOpen-weight models+2
スライド 4 枚14:29EN
Matthew Berman· 2023年5月8日A 2023 Google Memo on Open Models, LoRA and AI’s Competitive MoatMatthew Berman · Forward FutureMatthew Berman reviews a leaked employee essay arguing that rapid community iteration could challenge proprietary AI labs, and traces the early LLaMA ecosystem.Open-weight modelsAI Historyファインチューニング+1
スライド 2 枚6:53EN
Matthew Berman· 2023年5月4日StableVicuna’s 2023 Release: An Early RLHF Chatbot Put to the TestMatthew Berman · Forward FutureMatthew Berman reviews the 13-billion-parameter model and tests poetry, simple code, reasoning and a resignation email.Open-weight modelsReinforcement Learning評価(Evals)+1
スライド 4 枚9:58EN
Matthew Berman· 2023年4月26日HuggingChat’s 2023 Debut: Testing Writing, Reasoning and Python CodeMatthew Berman · Forward FutureMatthew Berman tries the early OpenAssistant-powered HuggingChat on writing, arithmetic, logic and a Snake game, then compares a few outputs with GPT-3.5 and GPT-4. The results illustrate both promise and limitations in this small historical test.Open-weight modelsBenchmarksモデルと学習+2
1:13:52EN
Matthew Berman· 2023年4月15日Andriy Mulyar on GPT4All, Data Quality and Open Local ModelsMatthew Berman, Andriy Mulyar · Forward FutureThe Nomic AI co-founder explains how GPT4All emerged, why training data matters, and the tradeoffs between local and centralized AI.Local inferenceOpen-weight modelsData quality & curation+2
40:25EN
No Priors: AI, Machine Learning, Tech, & Startups· 2023年4月6日ポッドキャスト · 2 人A 6-Billion-Parameter Clone of ChatGPT’s Core Trickホスト Sarah Guo, Elad GilDatabricks CTO Matei Zaharia tells Sarah Guo and Elad Gil how Dolly learned instruction-following on fifty times less data than GPT-3 — and why he would rather look facts up than bake them into a trillion-parameter network.モデルと学習Open-weight modelsファインチューニング+3
スライド 7 枚7:16EN
Matthew Berman· 2023年4月5日Setting Up Alpaca Turbo for Local Language Models: A 2023 TutorialMatthew Berman · Forward FutureMatthew Berman demonstrates an early ChatGPT-style interface for local Alpaca models, from the Conda setup to a short test on a Mac.Local inferenceOpen-weight modelsプロダクトと UX+1
スライド 5 枚8:05EN
Matthew Berman· 2023年3月29日A 2023 Guide to Running the Original GPT4All Model LocallyMatthew Berman · Forward FutureMatthew Berman demonstrates an early CPU-based GPT4All release, its terminal installation and the resources available for fine-tuning.Open-weight modelsモデルと学習インフラとデプロイ
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