Not Legal Advice on AI Training Data in Japan
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leonardlin
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Interesting, I've just seen the my first HF spam on one of my new model uploads:
shisa-ai/shisa-v1-llama3-70b - someone has an SEO spam page as a HF space attached to the model!?! Wild. Who do I report this to?
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For those with an interest in JA language models, this Llama 3 70B test ablation looks like it is the current strongest publicly released, commercially usable, open model available. A lot of caveats I know, but it also matches
shisa-ai/shisa-v1-llama3-70b
augmxnt/ultra-orca-boros-en-ja-v1
gpt-3.5-turbo-0125's JA performance, which is worth noting, and is tuned *exclusively* with the old shisa-v1 dataset (so it's chart position will be very short lived).shisa-ai/shisa-v1-llama3-70b
augmxnt/ultra-orca-boros-en-ja-v1
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LLM in a flash: Efficient Large Language Model Inference with Limited Memory
Paper • 2312.11514 • Published • 253 -
PowerInfer: Fast Large Language Model Serving with a Consumer-grade GPU
Paper • 2312.12456 • Published • 40 -
Accelerating LLM Inference with Staged Speculative Decoding
Paper • 2308.04623 • Published • 20 -
LLM.int8(): 8-bit Matrix Multiplication for Transformers at Scale
Paper • 2208.07339 • Published • 4
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QuIP: 2-Bit Quantization of Large Language Models With Guarantees
Paper • 2307.13304 • Published • 1 -
SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression
Paper • 2306.03078 • Published • 2 -
OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models
Paper • 2308.13137 • Published • 14 -
AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration
Paper • 2306.00978 • Published • 5
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