#qwen2 — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #qwen2, aggregated by home.social.
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The #OpenCode is working. Check when the Nvidia is used for it
⎿ [Image #1]● I'll check how #Ollama uses the #Nvidia GPU.
● Bash(nvidia-smi --query-gpu=name,memory.used,memory.total,utilization.gpu --format=csv,noheader 2>/dev/null)
⎿ NVIDIA GeForce RTX 2060, 952 MiB, 6144 MiB, 9 %● Bash(ollama ps 2>/dev/null)
⎿ NAME ID SIZE PROCESSOR UNTIL
qwen2.5-coder:7b-16k 0533dd01f237 7.2 GB 30%/70% CPU/GPU 4 minutes from now● The model is currently loaded and actively using the GPU. Here's the breakdown:
- Model: #qwen2.5-coder:7b-16k — 7.2 GB total
- Split: 30% CPU / 70% GPU — the model is split across RAM and VRAM because it doesn't fit entirely in the RTX 2060's 6 GB VRAM
- Current #GPU #VRAM usage: 952 MiB used of 6144 MiB (the rest of the model layers sit in system RAM)
- GPU compute utilization: 9% right now (idle between requests)The GPU is used whenever OpenCode sends a prompt to Ollama — during inference, 70% of the model layers run on the #RTX2060 and 30% on the #CPU. The model stays loaded in VRAM for 4 more minutes of idle time before Ollama unloads it.
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The #OpenCode is working. Check when the Nvidia is used for it
⎿ [Image #1]● I'll check how #Ollama uses the #Nvidia GPU.
● Bash(nvidia-smi --query-gpu=name,memory.used,memory.total,utilization.gpu --format=csv,noheader 2>/dev/null)
⎿ NVIDIA GeForce RTX 2060, 952 MiB, 6144 MiB, 9 %● Bash(ollama ps 2>/dev/null)
⎿ NAME ID SIZE PROCESSOR UNTIL
qwen2.5-coder:7b-16k 0533dd01f237 7.2 GB 30%/70% CPU/GPU 4 minutes from now● The model is currently loaded and actively using the GPU. Here's the breakdown:
- Model: #qwen2.5-coder:7b-16k — 7.2 GB total
- Split: 30% CPU / 70% GPU — the model is split across RAM and VRAM because it doesn't fit entirely in the RTX 2060's 6 GB VRAM
- Current #GPU #VRAM usage: 952 MiB used of 6144 MiB (the rest of the model layers sit in system RAM)
- GPU compute utilization: 9% right now (idle between requests)The GPU is used whenever OpenCode sends a prompt to Ollama — during inference, 70% of the model layers run on the #RTX2060 and 30% on the #CPU. The model stays loaded in VRAM for 4 more minutes of idle time before Ollama unloads it.
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The #OpenCode is working. Check when the Nvidia is used for it
⎿ [Image #1]● I'll check how #Ollama uses the #Nvidia GPU.
● Bash(nvidia-smi --query-gpu=name,memory.used,memory.total,utilization.gpu --format=csv,noheader 2>/dev/null)
⎿ NVIDIA GeForce RTX 2060, 952 MiB, 6144 MiB, 9 %● Bash(ollama ps 2>/dev/null)
⎿ NAME ID SIZE PROCESSOR UNTIL
qwen2.5-coder:7b-16k 0533dd01f237 7.2 GB 30%/70% CPU/GPU 4 minutes from now● The model is currently loaded and actively using the GPU. Here's the breakdown:
- Model: #qwen2.5-coder:7b-16k — 7.2 GB total
- Split: 30% CPU / 70% GPU — the model is split across RAM and VRAM because it doesn't fit entirely in the RTX 2060's 6 GB VRAM
- Current #GPU #VRAM usage: 952 MiB used of 6144 MiB (the rest of the model layers sit in system RAM)
- GPU compute utilization: 9% right now (idle between requests)The GPU is used whenever OpenCode sends a prompt to Ollama — during inference, 70% of the model layers run on the #RTX2060 and 30% on the #CPU. The model stays loaded in VRAM for 4 more minutes of idle time before Ollama unloads it.
-
The #OpenCode is working. Check when the Nvidia is used for it
⎿ [Image #1]● I'll check how #Ollama uses the #Nvidia GPU.
● Bash(nvidia-smi --query-gpu=name,memory.used,memory.total,utilization.gpu --format=csv,noheader 2>/dev/null)
⎿ NVIDIA GeForce RTX 2060, 952 MiB, 6144 MiB, 9 %● Bash(ollama ps 2>/dev/null)
⎿ NAME ID SIZE PROCESSOR UNTIL
qwen2.5-coder:7b-16k 0533dd01f237 7.2 GB 30%/70% CPU/GPU 4 minutes from now● The model is currently loaded and actively using the GPU. Here's the breakdown:
- Model: #qwen2.5-coder:7b-16k — 7.2 GB total
- Split: 30% CPU / 70% GPU — the model is split across RAM and VRAM because it doesn't fit entirely in the RTX 2060's 6 GB VRAM
- Current #GPU #VRAM usage: 952 MiB used of 6144 MiB (the rest of the model layers sit in system RAM)
- GPU compute utilization: 9% right now (idle between requests)The GPU is used whenever OpenCode sends a prompt to Ollama — during inference, 70% of the model layers run on the #RTX2060 and 30% on the #CPU. The model stays loaded in VRAM for 4 more minutes of idle time before Ollama unloads it.
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The #OpenCode is working. Check when the Nvidia is used for it
⎿ [Image #1]● I'll check how #Ollama uses the #Nvidia GPU.
● Bash(nvidia-smi --query-gpu=name,memory.used,memory.total,utilization.gpu --format=csv,noheader 2>/dev/null)
⎿ NVIDIA GeForce RTX 2060, 952 MiB, 6144 MiB, 9 %● Bash(ollama ps 2>/dev/null)
⎿ NAME ID SIZE PROCESSOR UNTIL
qwen2.5-coder:7b-16k 0533dd01f237 7.2 GB 30%/70% CPU/GPU 4 minutes from now● The model is currently loaded and actively using the GPU. Here's the breakdown:
- Model: #qwen2.5-coder:7b-16k — 7.2 GB total
- Split: 30% CPU / 70% GPU — the model is split across RAM and VRAM because it doesn't fit entirely in the RTX 2060's 6 GB VRAM
- Current #GPU #VRAM usage: 952 MiB used of 6144 MiB (the rest of the model layers sit in system RAM)
- GPU compute utilization: 9% right now (idle between requests)The GPU is used whenever OpenCode sends a prompt to Ollama — during inference, 70% of the model layers run on the #RTX2060 and 30% on the #CPU. The model stays loaded in VRAM for 4 more minutes of idle time before Ollama unloads it.
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RT @HuggingModels: Lernen Sie Qwen2-32B-N64-Decomp kennen, eine leistungsstarke konversationelle KI, die ab sofort im GGUF-Format verfügbar ist. Dieses Modell bringt Dialogfunktionen auf Enterprise-Niveau auf lokale Maschinen und ermöglicht es Ihnen, anspruchsvolle KI-Chats ohne Cloud-Abhängigkeiten zu führen. Perfekt für Entwickler, die volle Kontrolle wünschen.
mehr auf Arint.info
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RT @HuggingModels: Lernen Sie Qwen2-32B-N64-Decomp kennen, eine leistungsstarke konversationelle KI, die ab sofort im GGUF-Format verfügbar ist. Dieses Modell bringt Dialogfunktionen auf Enterprise-Niveau auf lokale Maschinen und ermöglicht es Ihnen, anspruchsvolle KI-Chats ohne Cloud-Abhängigkeiten zu führen. Perfekt für Entwickler, die volle Kontrolle wünschen.
mehr auf Arint.info
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BTW, these are the #AI #LLM models I settled on using with #JanAI:
#Qwen2.5 at 0.5B (Qwen2_5-0_5B-Instruct-uncensored_Q8_0), for fastest performance on low-end hardware
#Qwen2 at 1.5B (Qwen2-1_5B-Instruct-Abliterated-Q5_K_M), for balanced performance and good enough output quality
#Llama3.2 at 3B (Llama-3_2-3B-Instruct-heretic-ablitered-uncensored_Q5_K_M), for higher quality output
#Llama3 actually doesn’t run too poorly on my machine, although it can take some time to load up responses sometimes.
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BTW, these are the #AI #LLM models I settled on using with #JanAI:
#Qwen2.5 at 0.5B (Qwen2_5-0_5B-Instruct-uncensored_Q8_0), for fastest performance on low-end hardware
#Qwen2 at 1.5B (Qwen2-1_5B-Instruct-Abliterated-Q5_K_M), for balanced performance and good enough output quality
#Llama3.2 at 3B (Llama-3_2-3B-Instruct-heretic-ablitered-uncensored_Q5_K_M), for higher quality output
#Llama3 actually doesn’t run too poorly on my machine, although it can take some time to load up responses sometimes.
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BTW, these are the #AI #LLM models I settled on using with #JanAI:
#Qwen2.5 at 0.5B (Qwen2_5-0_5B-Instruct-uncensored_Q8_0), for fastest performance on low-end hardware
#Qwen2 at 1.5B (Qwen2-1_5B-Instruct-Abliterated-Q5_K_M), for balanced performance and good enough output quality
#Llama3.2 at 3B (Llama-3_2-3B-Instruct-heretic-ablitered-uncensored_Q5_K_M), for higher quality output
#Llama3 actually doesn’t run too poorly on my machine, although it can take some time to load up responses sometimes.
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Fine-tuned Qwen2.5-7B on 100 films for probabilistic story graphs
#HackerNews #Fine-tuned #Qwen2.5-7B #films #storygraphs #AI #cinegraphs
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Fine-tuned Qwen2.5-7B on 100 films for probabilistic story graphs
#HackerNews #Fine-tuned #Qwen2.5-7B #films #storygraphs #AI #cinegraphs
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Fine-tuned Qwen2.5-7B on 100 films for probabilistic story graphs
#HackerNews #Fine-tuned #Qwen2.5-7B #films #storygraphs #AI #cinegraphs
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Fine-tuned Qwen2.5-7B on 100 films for probabilistic story graphs
#HackerNews #Fine-tuned #Qwen2.5-7B #films #storygraphs #AI #cinegraphs
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Fine-tuned Qwen2.5-7B on 100 films for probabilistic story graphs
#HackerNews #Fine-tuned #Qwen2.5-7B #films #storygraphs #AI #cinegraphs
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Vấn đề với hệ thống chat RAG: Qwen2.5 bỏ qua ngữ cảnh cuộc trò chuyện trước và trả lời không liên quan cho các câu hỏi tiếp theo. Người dùng gặp khó khăn khi mô hình chỉ dựa vào truy vấn mới nhất thay vì sử dụng lịch sử chat.
#RAG #AI #Qwen2.5 #Chatbot #LỗiKỹThuật
https://www.reddit.com/r/ollama/comments/1p52b8z/rag_followups_not_working_qwen25_ignores_previous/
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Hướng dẫn tinh chỉnh mô hình Qwen2.5-Coder-1.5B cho phân tích cảm xúc tiếng Trung. Có thể chạy trên Google Colab miễn phí trong 20-30 phút. Độ chính xác tăng từ 91,6% lên 97,8%. #AI #MachineLearning #Qwen2.5 #PhânTíchCảmXúc #GoogleColab #TinhChỉnhMôHình #TríTuệNhânTạo #HọcMáy
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https://www.europesays.com/ie/154483/ Brewlander lets fans direct their own beer ads with AI prompts #AiAdvertising #AiBeerAds #beer #BlkjHavas #brewlander #CraftBeerMarketing #DiyBeerCommercials #Éire #IE #IndependentBrewer #InnovativeBeerCampaigns #Ireland #Qwen2.5 #SingaporeCraftBeer #SingaporeGypsyBrewer #SoraAi #Technology #TextToVideoAi #UserGeneratedContent
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Ch peque nhá! Tôi vừa chuyển sang dùng Qwen2.5 Code Instruct bản tự-host thành công! M المقابل với Claude đầu tiên (lần nào 1h phải chờ), Qwen2.5 có thể xử lý comuni code, debug, và nhiếp ý nhanh lùi ởстром đường công việc. Ưbrochen ở máy MBook Pro 48GB và PC 2x RTX 5060TI 16GB (không cần quantize). Cài đặt đơn giản, chất lượng tốt cho công việc lẻ lậu.
Tham khảo GitHub: @reliableJARED/qwen_coder
Tags: #AI #Qwen2.5 #CodeAssistant #LocalTech #MáyTínhLâu
#TechTips #OfflineAI #DevelopersCommu -
🧠 #ByteDance ha rilasciato UI-TARS-1.5, un agente multimodale basato su #Qwen2.5-VL-7B che unisce visione e linguaggio con "reasoning".
👉 I dettagli: https://www.linkedin.com/posts/alessiopomaro_bytedance-qwen2-claude-activity-7321413516488286208-YtOI
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✉️ 𝗦𝗲 𝘃𝘂𝗼𝗶 𝗿𝗶𝗺𝗮𝗻𝗲𝗿𝗲 𝗮𝗴𝗴𝗶𝗼𝗿𝗻𝗮𝘁𝗼/𝗮 𝘀𝘂 𝗾𝘂𝗲𝘀𝘁𝗲 𝘁𝗲𝗺𝗮𝘁𝗶𝗰𝗵𝗲, 𝗶𝘀𝗰𝗿𝗶𝘃𝗶𝘁𝗶 𝗮𝗹𝗹𝗮 𝗺𝗶𝗮 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿: https://bit.ly/newsletter-alessiopomaro
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🧠 #ByteDance ha rilasciato UI-TARS-1.5, un agente multimodale basato su #Qwen2.5-VL-7B che unisce visione e linguaggio con "reasoning".
👉 I dettagli: https://www.linkedin.com/posts/alessiopomaro_bytedance-qwen2-claude-activity-7321413516488286208-YtOI
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✉️ 𝗦𝗲 𝘃𝘂𝗼𝗶 𝗿𝗶𝗺𝗮𝗻𝗲𝗿𝗲 𝗮𝗴𝗴𝗶𝗼𝗿𝗻𝗮𝘁𝗼/𝗮 𝘀𝘂 𝗾𝘂𝗲𝘀𝘁𝗲 𝘁𝗲𝗺𝗮𝘁𝗶𝗰𝗵𝗲, 𝗶𝘀𝗰𝗿𝗶𝘃𝗶𝘁𝗶 𝗮𝗹𝗹𝗮 𝗺𝗶𝗮 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿: https://bit.ly/newsletter-alessiopomaro
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🧠 #ByteDance ha rilasciato UI-TARS-1.5, un agente multimodale basato su #Qwen2.5-VL-7B che unisce visione e linguaggio con "reasoning".
👉 I dettagli: https://www.linkedin.com/posts/alessiopomaro_bytedance-qwen2-claude-activity-7321413516488286208-YtOI
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✉️ 𝗦𝗲 𝘃𝘂𝗼𝗶 𝗿𝗶𝗺𝗮𝗻𝗲𝗿𝗲 𝗮𝗴𝗴𝗶𝗼𝗿𝗻𝗮𝘁𝗼/𝗮 𝘀𝘂 𝗾𝘂𝗲𝘀𝘁𝗲 𝘁𝗲𝗺𝗮𝘁𝗶𝗰𝗵𝗲, 𝗶𝘀𝗰𝗿𝗶𝘃𝗶𝘁𝗶 𝗮𝗹𝗹𝗮 𝗺𝗶𝗮 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿: https://bit.ly/newsletter-alessiopomaro
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🧠 #ByteDance ha rilasciato UI-TARS-1.5, un agente multimodale basato su #Qwen2.5-VL-7B che unisce visione e linguaggio con "reasoning".
👉 I dettagli: https://www.linkedin.com/posts/alessiopomaro_bytedance-qwen2-claude-activity-7321413516488286208-YtOI
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✉️ 𝗦𝗲 𝘃𝘂𝗼𝗶 𝗿𝗶𝗺𝗮𝗻𝗲𝗿𝗲 𝗮𝗴𝗴𝗶𝗼𝗿𝗻𝗮𝘁𝗼/𝗮 𝘀𝘂 𝗾𝘂𝗲𝘀𝘁𝗲 𝘁𝗲𝗺𝗮𝘁𝗶𝗰𝗵𝗲, 𝗶𝘀𝗰𝗿𝗶𝘃𝗶𝘁𝗶 𝗮𝗹𝗹𝗮 𝗺𝗶𝗮 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿: https://bit.ly/newsletter-alessiopomaro
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🧠 #ByteDance ha rilasciato UI-TARS-1.5, un agente multimodale basato su #Qwen2.5-VL-7B che unisce visione e linguaggio con "reasoning".
👉 I dettagli: https://www.linkedin.com/posts/alessiopomaro_bytedance-qwen2-claude-activity-7321413516488286208-YtOI
___
✉️ 𝗦𝗲 𝘃𝘂𝗼𝗶 𝗿𝗶𝗺𝗮𝗻𝗲𝗿𝗲 𝗮𝗴𝗴𝗶𝗼𝗿𝗻𝗮𝘁𝗼/𝗮 𝘀𝘂 𝗾𝘂𝗲𝘀𝘁𝗲 𝘁𝗲𝗺𝗮𝘁𝗶𝗰𝗵𝗲, 𝗶𝘀𝗰𝗿𝗶𝘃𝗶𝘁𝗶 𝗮𝗹𝗹𝗮 𝗺𝗶𝗮 𝗻𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿: https://bit.ly/newsletter-alessiopomaro
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Qwen2.5-VL & QVQ-Max: Neue Maßstäbe in der visuellen KI
Fortschrittliche Bild- und Videoanalyse
Präzise Objekterkennung
Verbesserte Dokumentenverarbeitung#ai #ki #artificialintelligence #kuenstlicheintelligenz #Qwen2.5-VL #QVQ-Max
Jetzt lesen und folgen!
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Qwen2.5-VL & QVQ-Max: Neue Maßstäbe in der visuellen KI
Fortschrittliche Bild- und Videoanalyse
Präzise Objekterkennung
Verbesserte Dokumentenverarbeitung#ai #ki #artificialintelligence #kuenstlicheintelligenz #Qwen2.5-VL #QVQ-Max
Jetzt lesen und folgen!
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Qwen2.5-VL & QVQ-Max: Neue Maßstäbe in der visuellen KI
Fortschrittliche Bild- und Videoanalyse
Präzise Objekterkennung
Verbesserte Dokumentenverarbeitung#ai #ki #artificialintelligence #kuenstlicheintelligenz #Qwen2.5-VL #QVQ-Max
Jetzt lesen und folgen!
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Qwen2.5-VL & QVQ-Max: Neue Maßstäbe in der visuellen KI
Fortschrittliche Bild- und Videoanalyse
Präzise Objekterkennung
Verbesserte Dokumentenverarbeitung#ai #ki #artificialintelligence #kuenstlicheintelligenz #Qwen2.5-VL #QVQ-Max
Jetzt lesen und folgen!
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Qwen2.5-VL & QVQ-Max: Neue Maßstäbe in der visuellen KI
Fortschrittliche Bild- und Videoanalyse
Präzise Objekterkennung
Verbesserte Dokumentenverarbeitung#ai #ki #artificialintelligence #kuenstlicheintelligenz #Qwen2.5-VL #QVQ-Max
Jetzt lesen und folgen!
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Alibaba Cloud shakes up the AI scene with **Qwen2.5-Omni-7B!** This cutting-edge multimodal model processes text, images, audio, and video, making it perfect for mobile devices. It's designed for cost-effective AI agents, especially in voice applications for the visually impaired. With a hefty **$53 billion** investment in AI and cloud infrastructure, Alibaba is positioning itself for success in the booming AI market—don’t miss the full story. [Read more](https://www.cnbc.com/2025/03/27/alibaba-launches-open-source-ai-model-for-cost-effective-ai-agents.html) #ArtificialIntelligence #AlibabaCloud #Qwen2 #TechInnovation
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Alibaba Cloud shakes up the AI scene with **Qwen2.5-Omni-7B!** This cutting-edge multimodal model processes text, images, audio, and video, making it perfect for mobile devices. It's designed for cost-effective AI agents, especially in voice applications for the visually impaired. With a hefty **$53 billion** investment in AI and cloud infrastructure, Alibaba is positioning itself for success in the booming AI market—don’t miss the full story. [Read more](https://www.cnbc.com/2025/03/27/alibaba-launches-open-source-ai-model-for-cost-effective-ai-agents.html) #ArtificialIntelligence #AlibabaCloud #Qwen2 #TechInnovation
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Alibaba Cloud shakes up the AI scene with **Qwen2.5-Omni-7B!** This cutting-edge multimodal model processes text, images, audio, and video, making it perfect for mobile devices. It's designed for cost-effective AI agents, especially in voice applications for the visually impaired. With a hefty **$53 billion** investment in AI and cloud infrastructure, Alibaba is positioning itself for success in the booming AI market—don’t miss the full story. [Read more](https://www.cnbc.com/2025/03/27/alibaba-launches-open-source-ai-model-for-cost-effective-ai-agents.html) #ArtificialIntelligence #AlibabaCloud #Qwen2 #TechInnovation
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Alibaba Cloud shakes up the AI scene with **Qwen2.5-Omni-7B!** This cutting-edge multimodal model processes text, images, audio, and video, making it perfect for mobile devices. It's designed for cost-effective AI agents, especially in voice applications for the visually impaired. With a hefty **$53 billion** investment in AI and cloud infrastructure, Alibaba is positioning itself for success in the booming AI market—don’t miss the full story. [Read more](https://www.cnbc.com/2025/03/27/alibaba-launches-open-source-ai-model-for-cost-effective-ai-agents.html) #ArtificialIntelligence #AlibabaCloud #Qwen2 #TechInnovation
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Qwen2.5-VL-32B: because nothing says "cutting-edge" like moaning about parameter scales and reinforcement learning 🙄. Apparently, this 32B thing is "smarter" and "lighter" – sounds like a diet ad for AI models. 😂🍩 #Innovation!
https://qwenlm.github.io/blog/qwen2.5-vl-32b/ #Qwen2.5VL32B #AIModels #ReinforcementLearning #CuttingEdge #TechHumor #HackerNews #ngated -
Qwen2.5-VL-32B: because nothing says "cutting-edge" like moaning about parameter scales and reinforcement learning 🙄. Apparently, this 32B thing is "smarter" and "lighter" – sounds like a diet ad for AI models. 😂🍩 #Innovation!
https://qwenlm.github.io/blog/qwen2.5-vl-32b/ #Qwen2.5VL32B #AIModels #ReinforcementLearning #CuttingEdge #TechHumor #HackerNews #ngated -
Qwen2.5-VL-32B: because nothing says "cutting-edge" like moaning about parameter scales and reinforcement learning 🙄. Apparently, this 32B thing is "smarter" and "lighter" – sounds like a diet ad for AI models. 😂🍩 #Innovation!
https://qwenlm.github.io/blog/qwen2.5-vl-32b/ #Qwen2.5VL32B #AIModels #ReinforcementLearning #CuttingEdge #TechHumor #HackerNews #ngated -
Qwen2.5-VL-32B: because nothing says "cutting-edge" like moaning about parameter scales and reinforcement learning 🙄. Apparently, this 32B thing is "smarter" and "lighter" – sounds like a diet ad for AI models. 😂🍩 #Innovation!
https://qwenlm.github.io/blog/qwen2.5-vl-32b/ #Qwen2.5VL32B #AIModels #ReinforcementLearning #CuttingEdge #TechHumor #HackerNews #ngated -
Qwen2.5-VL-32B: Smarter and Lighter
https://qwenlm.github.io/blog/qwen2.5-vl-32b/
#HackerNews #Qwen2.5VL32B #Smarter #Lighter #AI #Technology #Innovation
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Qwen2.5-VL-32B: Smarter and Lighter
https://qwenlm.github.io/blog/qwen2.5-vl-32b/
#HackerNews #Qwen2.5VL32B #Smarter #Lighter #AI #Technology #Innovation
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Qwen2.5-VL-32B: Smarter and Lighter
https://qwenlm.github.io/blog/qwen2.5-vl-32b/
#HackerNews #Qwen2.5VL32B #Smarter #Lighter #AI #Technology #Innovation
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Qwen2.5-VL-32B: Smarter and Lighter
https://qwenlm.github.io/blog/qwen2.5-vl-32b/
#HackerNews #Qwen2.5VL32B #Smarter #Lighter #AI #Technology #Innovation
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Testing Deepseek-r1 on Ollama:
https://www.glukhov.org/post/2025/02/deepseek-r1-on-ollama/
#Deepseek-r1 #Ollama #qwen2.5 #llama31
