Ruff ci (#194)
Ruff ci (#194) * apply ruff * rename * specify ruff version for CI * also check imports * check formatting
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Extending the Context Length to 1M Tokens!
API Documentation (Chinese) HuggingFace Demo ModelScope Demo Introduction After the release of Qwen2.5, we heard the community’s demand for processing longer contexts. In recent months, we…
Does the UK’s liver transplant matching algorithm systematically exclude younger patients?
Seemingly minor technical decisions can have life-or-death effects
Qwen2.5-Coder Series: Powerful, Diverse, Practical.
GITHUB HUGGING FACE MODELSCOPE KAGGLE DEMO DISCORD Introduction Today, we are excited to open source the “Powerful”, “Diverse”, and “Practical” Qwen2.5-Coder series, dedicated to continuously promoting…
Merge pull request #619 from 01-ai/Anonymitaet-patch-2
Merge pull request #619 from 01-ai/Anonymitaet-patch-2 Update README.md
Partially rewriting an LLM in natural language
Using interpretations of SAE latents to simulate activations.
We’re moving our blog!
We’re excited to announce that our blog is moving to its new home! From now on, all our new blog posts will be published directly on…
Merge pull request #618 from 01-ai/Haijian06-patch-2
Merge pull request #618 from 01-ai/Haijian06-patch-2 Update README.md
39 Lessons on Building ML Systems, Scaling, Execution, and More
ML systems, production & scaling, execution & collaboration, building for users, conference etiquette.
🌍Exciting news from our developer community! We're thrilled to share a blog on Refactor Earth, which explores an innovative approach to sustainable…
🌍Exciting news from our developer community!We're thrilled to share a blog on Refactor Earth, which explores an innovative approach to sustainable AI. By combining Yi-Large and…
Third-party evaluation to identify risks in LLMs’ training data
An overview of the minetester and preliminary work
Thrilled to see such widespread adoption of Yi! Huge thanks to @huggingface, @ollama, and mradermacher for your incredible support! ollama run hf(.)co…
Thrilled to see such widespread adoption of Yi!Huge thanks to @huggingface, @ollama, and mradermacher for your incredible support!ollama run hf(.)co/mradermacher/Yi-1.5-34B-Chat-16K-GGUF#Yi34B #LLM #AIJulien Chaumond: The @ollama -…
Using LLM-as-a-Judge For Evaluation: A Complete Guide
Using LLM-as-a-Judge For Evaluation: A Complete Guide
Hybrid Preferences: Learning to Route Instances for Human vs. AI Feedback
Much of the recent advancements in large language models (LLMs) have been powered by human feedback, usually in the form of preference datasets. Think of preferences…
AlignEval: Building an App to Make Evals Easy, Fun, and Automated
Look at and label your data, build and evaluate your LLM-evaluator, and optimize it against your labels.
Applying Theory of Mind: Can AI Understand and Predict Human Behavior?
“Theory of Mind” (ToM) is the ability to understand that others have their own thoughts and beliefs, even when they differ from ours — a skill…
Ai2 at COP 16: Harnessing AI and Conservation Tech to Protect Our Planet
Empowering conservation efforts through innovative technologies and global collaborationA vessel captured by NASA’s Landsat 8. Skylight’s computer vision models leverage this imagery to identify suspicious behavior,…
We are proud to present the latest model ⚡️Yi-Lightning ⚡️ now #6 in the world, higher than the original GPT-4o released 5 months ago. Also humble…
We are proud to present the latest model ⚡️Yi-Lightning ⚡️ now #6 in the world, higher than the original GPT-4o released 5 months ago. Also humbled…
We're thrilled to unveil Yi-Lightning and Yi-Lightning-Lite, our latest proprietary models! Both are now accessible via API at https://platform.lingyi…
We're thrilled to unveil Yi-Lightning and Yi-Lightning-Lite, our latest proprietary models! Both are now accessible via API at https://platform.lingyiwanwu.com and featured in @lmarena_ai's Chatbot Arena (https://lmarena.ai/).…
Mechanistic Anomaly Detection Research Update 2
Interim report on ongoing work on mechanistic anomaly detection
RLHF and RLAIF in GPT-NeoX
GPT-NeoX now supports post-training thanks to a collaboration with SynthLabs.
FAQ about the book and our writing process
What's in the book and how we wrote it
Investigating Pretraining Dynamics and Stability with OLMo Checkpoints
A central goal of the OLMo project is to use our experience to contribute to an open science of LM pretraining to provide a foundation for…
Separating code reasoning and editing
An Architect model describes how to solve the coding problem, and an Editor model translates that into file edits. This Architect/Editor approach produces SOTA benchmark results.