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xianbao  authored a paper 6 months ago
PIN: A Knowledge-Intensive Dataset for Paired and Interleaved Multimodal Documents
xianbao  updated a Space 7 months ago
my-test-org-xianbao/README
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my-test-org-xianbao's activity

xianbao 
posted an update 4 months ago
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1693
With the open-weight release of CogVideoX-5B from THUDM, i.e. GLM team, the Video Generation Model (how about calling it VGM) field has officially became the next booming "LLM"

What does the landscape look like? What are other video generation models? This collection below is all your need.

xianbao/video-generation-models-66c350163c74f60f5c412af6

The above video is generated by @a-r-r-o-w with CogVideoX-5B, taken from a nice lookout for the field!
xianbao 
authored a paper 6 months ago
xianbao 
updated a Space 7 months ago
xianbao 
posted an update 7 months ago
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1781
Why Apache 2.0 Matters for LLMs 🤔

@01AI_Yi recently switched from a permissive & commercially friendly license, to Apache 2.0. And the community loved it! 🚀

@JustinLin610 also had a poll on model license and the majority votes for Apache 2.0.

Why it is a Big Deal? ⬇️

📚 Legal Simplicity: Custom licenses need costly & time-consuming legal review. Apache 2.0 is well-known & easier for legal teams to handle.

👩‍💻 Developer-Friendly: Legal docs are a pain for devs! Apache 2.0 is well-known and tech-friendly, making it easier for non-native developers to understand the implications too.

🔗 Easier Integration: Apache 2.0 is compatible with many other licenses, simplifying tasks like model merging with models of different licensing requirements.

🚫 No Permission Needed: Custom licenses often require explicit permission and additional documentation work of filling forms, creating barriers. Apache 2.0 removes this hurdle, letting devs focus on innovation.

There are a lot interesting discussions from
@JustinLin610 's poll: https://x.com/JustinLin610/status/1793559737482764375 which inspired this thread.

Any other thoughts? Let me know ^^
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xianbao 
posted an update 7 months ago
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1213
DeepSeekV2 is a big deal. Not only because its significant improvements to both key components of Transformer: the Attention layer and FFN layer.

It has also completed disrupted the Chines LLM market and forcing the competitors to drop the price to 1% of the original price.

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There are two key components in Transformer architecture: the self-attention layer, which captures relationships between tokens in context, and the Feed-Forward Network (FFN) layer, which stores knowledge.

DeepSeek V2 introduces optimizations to both:

Attention layer normally uses KV Cache to reduce repetitive compute, but it consumes significant GPU RAM, limiting concurrent requests. DeepSeek V2 introduces Multi-head Latent Attention (MLA), which stores only a small latent representation, resulting in substantial RAM savings.

DeepSeek V2 utilizes 162 experts instead of the usual 8 as in Mixtral. This approach segments experts into finer granularity for higher specialization and more accurate knowledge acquisition. Activating only a small subset of experts for each token, leads to efficient processing.

It disrupted the market by dropping API prices to $0.14 per 1M tokens. This dramatic reduction forced competitors like GLM, Ernie, and QWen to follow suit, lowering their prices to 1% of their original offerings. Now, users can access these APIs at 1/35th the cost of ChatGPT-4o.
xianbao 
posted an update 8 months ago
xianbao 
posted an update 11 months ago
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Welcome Bunny! A family of lightweight but powerful multimodal models from BAAI

With detailed work on dataset curation, the Bunny-3B model built upon SigLIP and Phi-2 achieves performance on par with 13B models.

Model: BAAI/bunny-phi-2-siglip-lora

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xianbao 
posted an update 11 months ago
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There appears to be a huge misunderstanding regarding the licensing requirements for open sourced Chinese speaking speaking LLMs on
@huggingface


I initially shared this misconception too, but after conducting some research, I came up with the list below.

Veryimpressive!
xianbao 
posted an update 11 months ago
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Vision LLM for #edgecomputing ?

@openbmb , who OS'ed the UltraFeedback dataset before, released a series of strong eco-friendly yet powerful LLMs

- MiniCPM: 2B model that competes with Mistral-7B

- MiniCPM-V: 3B vision LLM on edge!
- MiniCPM-V: 3B vision LLM on edge!