2B: huggingface.co/Qwen/Qwen2-V...
7B: huggingface.co/Qwen/Qwen2-V...
72B: huggingface.co/Qwen/Qwen2-V...
2B: huggingface.co/Qwen/Qwen2-V...
7B: huggingface.co/Qwen/Qwen2-V...
72B: huggingface.co/Qwen/Qwen2-V...
- ColSmolVLM performs better than ColPali and DSE-Qwen2 on all English tasks
- ColSmolVLM is more memory efficient than ColQwen2 💗
Find the model here huggingface.co/vidore/colsm...
- ColSmolVLM performs better than ColPali and DSE-Qwen2 on all English tasks
- ColSmolVLM is more memory efficient than ColQwen2 💗
Find the model here huggingface.co/vidore/colsm...
@llamaindex.bsky.social released vdr-2b-multi-v1
> uses 70% less image tokens, yet outperforming other dse-qwen2 based models
> 3x faster inference with less VRAM 💨
> shrinkable with matryoshka 🪆
huggingface.co/collections/...
@llamaindex.bsky.social released vdr-2b-multi-v1
> uses 70% less image tokens, yet outperforming other dse-qwen2 based models
> 3x faster inference with less VRAM 💨
> shrinkable with matryoshka 🪆
huggingface.co/collections/...
ColQwen2 as retriever, MonoQwen2-VL as reranker, Qwen2-VL as VLM in this notebook that runs on a GPU as small as L4 🔥 huggingface.co/learn/cookbo...
ColQwen2 as retriever, MonoQwen2-VL as reranker, Qwen2-VL as VLM in this notebook that runs on a GPU as small as L4 🔥 huggingface.co/learn/cookbo...
https://gigazine.net/news/20240810-qwen2-math-ai-llm/
https://gigazine.net/news/20240810-qwen2-math-ai-llm/
1. lindy → deepseek v4
2. cursor → kimi k2.5
3. coinbase → glm-5.2 + kimi 2.7
4. shopify → qwen
5. airbnb → qwen
6. uber eats → qwen2
7. siemens → deepseek + qwen
8. chapsvision → qwen
9. microsoft → testing deepseek v4"
1. lindy → deepseek v4
2. cursor → kimi k2.5
3. coinbase → glm-5.2 + kimi 2.7
4. shopify → qwen
5. airbnb → qwen
6. uber eats → qwen2
7. siemens → deepseek + qwen
8. chapsvision → qwen
9. microsoft → testing deepseek v4"
github.com/intel/AI-Pla...
github.com/intel/AI-Pla...
A fully fledged LLM application using Qwen2-Instruct 1.5B, Scrapy, Stella embeddings model and hierarchical clustering in plain scipy!
A fully fledged LLM application using Qwen2-Instruct 1.5B, Scrapy, Stella embeddings model and hierarchical clustering in plain scipy!
Chat effortlessly with our flagship model Qwen2.5-Plus , explore vision-language capabilities with Qwen2-VL-Max , and dive into reasoning models like QwQ and QVQ, code with coding expert Qwen2.5-Coder-32B-Instruct, etc.
Chat effortlessly with our flagship model Qwen2.5-Plus , explore vision-language capabilities with Qwen2-VL-Max , and dive into reasoning models like QwQ and QVQ, code with coding expert Qwen2.5-Coder-32B-Instruct, etc.