The code of our paper "InfLLM: Unveiling the Intrinsic Capacity of LLMs for Understanding Extremely Long Sequences with Training-Free Memory"
Explore the capabilities of large language models for understanding long sequences without needing extensive training.
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Free · no card · unsubscribe anytimeThe code of our paper "InfLLM: Unveiling the Intrinsic Capacity of LLMs for Understanding Extremely Long Sequences with Training-Free Memory"
InfLLM has 407 stars on GitHub. It has been forked 40 times. InfLLM is written mainly in Python. It has been in active development since 2024. InfLLM is available under the MIT license. Its main topics are large-language-models, llm, long-context, training-free.
The code of our paper "InfLLM: Unveiling the Intrinsic Capacity of LLMs for Understanding Extremely Long Sequences with Training-Free Memory"
InfLLM is an open-source project. It is released under the MIT license.
Yes. InfLLM is free and open source — you can use, modify and self-host it.
InfLLM is available under the MIT license.
InfLLM is written mainly in Python.
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