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RWKV-CUDA Alternatives
Similar projects and alternatives to RWKV-CUDA
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RWKV-LM
RWKV is an RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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RWKV-v2-RNN-Pile
RWKV-v2-RNN trained on the Pile. See https://github.com/BlinkDL/RWKV-LM for details.
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token-shift-gpt
Implementation of Token Shift GPT - An autoregressive model that solely relies on shifting the sequence space for mixing
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AI-Writer
AI 写小说,生成玄幻和言情网文等等。中文预训练生成模型。采用我的 RWKV 模型,类似 GPT-2 。AI写作。RWKV for Chinese novel generation.
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RWKV-LM-LoRA
RWKV is a RNN with transformer-level LLM performance. It can be directly trained like a GPT (parallelizable). So it's combining the best of RNN and transformer - great performance, fast inference, saves VRAM, fast training, "infinite" ctx_len, and free sentence embedding.
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SaaSHub
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RWKV-CUDA reviews and mentions
- People who've used RWKV, whats your wishlist for it?
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Accelerate PyTorch with Taichi: Data Preprocessing & High-performance ML Operator Customization
This repo introduces an interesting example of customizing an ML operator in CUDA. The author developed an RWKV language model using sort of a one-dimensional depthwise convolution custom operator. The model in itself does not involve large amounts of computation, but still runs slow because PyTorch does not have native support for it. So, the author customized the operator in CUDA and used a set of optimization techniques, such as loop fusion and Shared Memory, achieving a performance 20x better than he did with PyTorch.
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[R] RWKV-v2-RNN : A parallelizable RNN with transformer-level LM performance, and without using attention
It's using my custom CUDA kernel ( https://github.com/BlinkDL/RWKV-CUDA ) to speedup training, so only GPU for now. On the other hand, you don't need CUDA for inference, and it is very fast even on CPUs.
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A note from our sponsor - SaaSHub
www.saashub.com | 10 May 2024
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The primary programming language of RWKV-CUDA is Cuda.
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