ollama
7.6K posts
ollama
@ollama
https://t.co/1JpLwJ93nX
California, USA Katılım Ağustos 2023
10 Takip Edilen131.9K Takipçiler
ASK YOUR MOTHER @socraticainfo (another fun sidequest)
we used @grok @ollama and @ElevenLabs to make a mean parent replicating chat interface that roasts and compares you
hooked it up with quick gimmicks - big red button, unexpectedly loud cop lights, handheld printer
Challenge: get your query blacklisted! (it's not that easy, go willlld)
blacklisted queries go on the wall of shame, the highest honor one can achieve ☺️
it was one of the busiest I've seen booths get, with multiple people asking me to publish so they can try it at home, and we had a 90%+ laugh rate after explaining what it is!
crowdsourced insults that helped train (thank you, ece uoft): docs.google.com/document/d/1Gv…
English
Last time Chinese models missed the SWE-rebench top 10, they got slammed for "benchmaxing." Now, GLM-5 is back in a very "interesting" spot.
Ibragim@ibragim_bad
🚨 SWE-rebench update! SWE-rebench is a live benchmark with fresh SWE tasks (issue+PR) from GitHub every month. updates: > we removed demonstrations and the 80-step limit (modern models can now handle huge contexts without getting trapped in loops!). > we added auxiliary interfaces for specific tasks like in SWE-bench-Pro to evaluate larger tasks fairly, ensuring valid solutions don't fail just because of mismatched test calls. insights: > Top models perform similarly. Among open-source options, GLM @Zai_org shows strong results, and StepFun @StepFun_ai is very cheap for its performance level ($0.14 per task). > GPT-5.4 shows high token efficiency, it ranks in the top 5 overall but uses the lowest number of tokens (774k per task) > Qwen3-Coder-Next & Step-3.5-Flash benefit massively from huge contexts. Qwen is an extreme case, averaging a wild 8.12M tokens. > We evaluated agentic harnesses (Claude Code, Codex, and Junie) and found a few things. Even in headless mode, they sometimes ask for additional context or attempt web searches. We explicitly disabled search and verified their curl commands to ensure they aren't just pulling solutions from the web. 🏆 You can find the full leaderboard here: swe-rebench.com 👾 Also, we launched our Discord! Join our leaderboard channel to discuss models, share ideas, ask questions, or report issues: discord.gg/V8FqXQ4CgU
English
ollama retweetledi
Nemotron-Cascade-2 is now available to run with Ollama.
ollama run nemotron-cascade-2
To run it locally with OpenClaw:
ollama launch openclaw --model nemotron-cascade-2
This model from NVIDIA delivers strong reasoning and agentic capabilities on par with models with up to 20x more parameters.
English
ollama retweetledi
@ayzekdiolar There's a PR for it already: github.com/aduermael/lang…
@ollama will be added soon! 🙂
(and it's actually the first external contribution! ✨)
English
I've been working on this humble Claude Code alternative. In a nutshell: containerized by default, multi-provider (Anthropic, OpenAI, Gemini & Grok so far), self-building dev environments & 100% open-source, 100% Go.
The repo is brand new, only 1 ⭐️, 🥲.
English
@MiniMax_AI @ollama ollama support is where a lot of these launches become real usage
English
M2.7 now live on @ollama 🚀
Built for real workflows -- just run it.
ollama@ollama
MiniMax-M2.7 is now available on Ollama's cloud. made for coding and agentic tasks 🖥️ Try it inside Claude Code: ollama launch claude --model minimax-m2.7:cloud 🦞 Use it with OpenClaw: ollama launch openclaw --model minimax-m2.7:cloud If you already have OpenClaw running, you can switch the model inside via: /model ollama/minimax-m2.7:cloud 🏃Run the model: ollama run minimax-m2.7:cloud
English
MiniMax-M2.7 is now available on Ollama's cloud.
made for coding and agentic tasks
🖥️ Try it inside Claude Code:
ollama launch claude --model minimax-m2.7:cloud
🦞 Use it with OpenClaw:
ollama launch openclaw --model minimax-m2.7:cloud
If you already have OpenClaw running, you can switch the model inside via:
/model ollama/minimax-m2.7:cloud
🏃Run the model:
ollama run minimax-m2.7:cloud
MiniMax (official)@MiniMax_AI
Introducing MiniMax-M2.7, our first model which deeply participated in its own evolution, with an 88% win-rate vs M2.5 - Production-Ready SWE: With SOTA performance in SWE-Pro (56.22%) and Terminal Bench 2 (57.0%), M2.7 reduced intervention-to-recovery time for online incidents to 3-min on certain occasions. - Advanced Agentic Abilities: Trained for Agent Teams and tool search tool, with 97% skill adherence across 40+ complex skills. M2.7 is on par with Sonnet 4.6 in OpenClaw. - Professional Workspace: SOTA in professional knowledge, supports multi-turn, high-fidelity Office file editing. MiniMax Agent: agent.minimax.io API: platform.minimax.io Token Plan: platform.minimax.io/subscribe/toke…
English
Nemotron 3 Nano 4B is now available to run via Ollama:
ollama run nemotron-3-nano:4b
Try it with Pi, the minimal agent runtime that powers OpenClaw:
ollama launch pi --model nemotron-3-nano:4b
This new addition to @nvidia's Nemotron family is a great fit for building and running agents on constrained hardware.
English