
InternLM
@intern_lm
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InternLM has open-sourced a 7 billion parameter base model and a chat model tailored for practical scenarios. Discord: https://t.co/GgISf3EmFE
Joined June 2023
🚀 Introducing #POLAR: Bring Reward Model into a New Pre-training Era! .✨ Say goodbye to reward models with poor generalization! POLAR (Policy Discriminative Learning) is a groundbreaking pre-training paradigm that trains reward models to distinguish policy distributions,
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🥳Trained through #InternBootcamp, #InternThinker now combines pro-level Go skills with transparent reasoning. 😉In each game, it acts as a patient, insightful coach—analyzing the board, comparing moves, and clearly explaining each decision. 🤗Try it now:
🥳Introducing #InternBootcamp, an easy-to-use and extensible library for training large reasoning models. Unlimited automatic question generation and result verification. Over 1,000 verifiable tasks covering logic, puzzles, algorithms, games, and more. 🤗
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🥳Introducing #InternBootcamp, an easy-to-use and extensible library for training large reasoning models. Unlimited automatic question generation and result verification. Over 1,000 verifiable tasks covering logic, puzzles, algorithms, games, and more. 🤗
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🥳Thrill to release the full RL training code of #OREAL! .😊Now you can fully reproduce the results of OREAL-7B/32B. Using #DeepSeek-R1-Distill-Qwen-32B, you can further obtain a model has 95.6 on MATH-500! .🤗Code: 🤗Based on:
🥳Introducing #OREAL, a new RL method for math reasoning. 😊With OREAL, a 7B model achieves 94.0 pass@1 on MATH-500, matching many 32B models, while OREAL-32B achieves 95.0 pass@1, surpassing #DeepSeek-R1 Distilled models. 🤗Paper/Model/Data:.
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RT @CamelAIOrg: 📢 We've just integrated InternLM's models into the 🐫 CAMEL-AI framework!. InternLM is a multilingual, multi-billion-paramet….
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RT @zhyncs42: I'm excited about the release of @intern_lm 3 8B Instruct. It's superior to Qwen 2.5 7B Instruct and Llama 3.1 8B Instruct, w….
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🥳🚀🥳Try it now on:
🚀Introducing InternLM3-8B-Instruct with Apache License 2.0. -Trained on only 4T tokens, saving more than 75% of the training cost. -Supports deep thinking for complex reasoning and normal mode for chat. Model:@huggingface.GitHub:.
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🚀Introducing InternLM3-8B-Instruct with Apache License 2.0. -Trained on only 4T tokens, saving more than 75% of the training cost. -Supports deep thinking for complex reasoning and normal mode for chat. Model:@huggingface.GitHub:.
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🥳Now, you can sign up and log in to try #InternThinker using your email or GitHub account! .🤗Direct link to InternThinker: 😊Tips:.To start a new conversation with InternThinker, simply click on "InternThinker" in the left sidebar.
🥳Introducing #InternThinker. 🤗A Powerful Reasoning Model!.🤗Advanced long-term thinking capabilities. 🤗Self-reflection and correction during reasoning. Outperforms in complex tasks like math, coding, and logic puzzles. 🥳Try it now at
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🥳Introducing #InternThinker. 🤗A Powerful Reasoning Model!.🤗Advanced long-term thinking capabilities. 🤗Self-reflection and correction during reasoning. Outperforms in complex tasks like math, coding, and logic puzzles. 🥳Try it now at
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RT @zhyncs42: Excited to have hosted the SGLang @lmsysorg talk yesterday with @GPU_MODE 's @marksaroufim and @hsu_byron. Thanks to FlashInf….
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🥳We have released our InternLM2.5 new models in 1.8B and 20B on @huggingface. 😉1.8B: Ultra-lightweight, high-performance, with great adaptability. 😉20B: More powerful, ideal for complex tasks. 😍Explore now!. Models:.GitHub:.
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RT @Gradio: ✨ MindSearch: Mimicking Human Minds for Deep AI research. MindSearch is an open-source AI Search Engine Framework with Perplexi….
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🥳Still waiting for #SearchGPT? Let's try MindSearch at MindSearch mimics human minds in complex web search by a multi-agent framework, which is fully.open-sourced now!.You can build it locally with API models like GPT-4o or open-source model InternLM2.5!
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