Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
- deep-learning
- protein-sequences
- protein-structure
- semi-supervised-learning
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Tasks Assessing Protein Embeddings (TAPE), a set of five biologically relevant semi-supervised learning tasks spread across different domains of protein biology.
A computer, compiled into the weights of a language model. An exact CPU inside Qwen3.5-4B, with Gated DeltaNet state as RAM.
The open-source policy-as-code software that provides analysis for Multi-Cloud and SaaS environments, you can get insight with natural language (powered by OpenAI).
A large language model (LLM) plugin for Neovim, provides commands to interact with LLM (like ChatGPT, Copilot, ChatGLM, kimi, deepseek, openrouter and local llms). Support Github models.
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:sunrise: A comprehensive, cutting-edge open-source framework for next-generation Transformers/LLM, with compute-matched benchmarking and a platform for autonomous architecture research.
Extract knowledge from all information sources using gpt and other language models. Index and make Q&A session with information sources.
One API for every LLM: 170+ providers through one client, with a Rust core and native bindings for every major language.
Official code for Agent-Reflex: Teaching Language Agents to Act Reflectively
Integrate with the latest language models, image generation, speech, and deep learning frameworks like ChatGPT, DALL·E, and Cohere using few java lines.
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Give topics & subtopics and generate wiki articles in markdown language with your openai api key
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Code and data for the paper "Evaluating German Transformer Language Models with Syntactic Agreement Tests" (Zaczynska et al., 2020)
A minimalistic codebase for training NLG models from HuggingFace Transformers using PyTorch Lightning.