Forgot to link the report: https://
github.com/deepseek-ai/De
epSeek-V3/blob/main/DeepSeek_V3.pdf
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OPEN SOURCE
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DeepSeek-V3 Report Released on GitHub
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Stellar AI Model Release with Checkpoints and Detailed Report
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Congratulations on the stellar release! The model checkpoints and a detailed report – truly Christmas is here!
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DeepSeek Technical Report: 14.8T Tokens, GPT-4o Performance
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The DeepSeek Technical Report is out!! Trained on 14.8 Trillion Tokens, outperforms all open-source models, comparable to GPT-4o and Claude-Sonnet-3.5 Key contributions: > Load Balancing Strategy: Introduced an auxiliary-loss-free approach to minimize performance
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Model Configuration and Next Predict Layers Parameter Discussion
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yeah, config.json + modeling looks pretty much the same. Still no reference of “num_nextn_predict_layers” in modeling
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DeepSeek Instruct Open Weight LLM Released on Hub
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Holy fuck! They also dropped the Instruct model on the Hub – that’s literally the same model that runs on DeepSeek Chat! That’s the best open weight LLM right now and second best on AiderBench (after o1) Now we wait for the model card!
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DeepSeek V3 now on HuggingFace
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Besides that, DeepSeek V3 is now available on HuggingFace https://
huggingface.co/deepseek-ai/De
epSeek-V3-Base
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DeepSeek v3 ranks best open-weight LLM in LiveBench
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LiveBench reported by r/LocalLlama – DeepSeek v3 is the BEST open weight LLM AND SECOND BEST non-reasoning LLM after `gemini-exp-1206`
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Model Checkpoint Configuration Values Analysis
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digging into config.json of both the model checkpoint here, these are actual values picked up by the model vs, defaults above:
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AI Community Wishlist: TTS, Whisper, GPT-3.5 Architecture
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here's my wishlist: 1. Text to Speech backbone (even a nerfed version would do tbh)
2. Better + faster, multilingual Whisper (ideally without the Enc-Dec architecture)
3. GPT 3.5 If none of the above, release some arch details, let the community cook! -
DeepSeek-V2.5-1210 Model Comparison Analysis
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I'm comparing w/ https://
huggingface.co/deepseek-ai/De
epSeek-V2.5-1210
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