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Dec 18, 2023 · We propose Hieros, a hierarchical policy that learns time abstracted world representations and imagines trajectories at multiple time scales in latent space.
Dec 18, 2023 · This paper introduces an innovative approach for the parametric and practical compression of LLMs based on reduced order modelling, which entails low-rank ...
Jan 16, 2024 · ... state RNNs by fixing the size of their hidden state ... [R] StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization.
Dec 24, 2023 · Extensive experiments demonstrate that DiffMorpher achieves starkly better image morphing effects than previous methods across a variety of object categories, ...
Jan 5, 2024 · [R] StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization. 29 upvotes · 3 comments. r/MachineLearning icon. r ...
Dec 14, 2023 · We study an analogy to this problem: can weak model supervision elicit the full capabilities of a much stronger model? We test this using a range of pretrained ...
Jan 11, 2024 · [R] StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization ... Modelling of Latent Features in Large Language Models.
Quantizing ONNX Model to int16 for Weights and Bias - Reddit
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Dec 10, 2023 · I am currently exploring the quantization of an ONNX model, aiming to convert both weights and biases from float32 to int16 precision.
Jan 23, 2024 · [R] StableSSM: Alleviating the Curse of Memory in State-space Models through Stable Reparameterization. 29 upvotes · 3 comments. r/Enneagram icon. r/Enneagram ...