InternLM2.5-7B-Chat: Open Sourcing Large Language Models with Unmatched Reasoning, Long-Context Handling, and Enhanced Tool Use
What is the InternLM2.5-7B-Chat model's parameter size?
The InternLM2.5-7B-Chat model has a parameter size of 7 billion.
What frameworks support the InternLM2.5-7B-Chat model?
The InternLM2.5-7B-Chat model is supported by frameworks such as llama.cpp, an open-source framework for Large Language Model (LLM) inference, and LMDeploy, a toolkit developed by the MMRazor and MMDeploy teams for compressing, deploying, and serving LLMs. These frameworks allow the model to be utilized locally and in the cloud across various hardware platforms.
How does InternLM2.5-7B-Chat handle long-context tasks?
InternLM2.5-7B-Chat handles long-context tasks by employing a 1M context window, which allows it to process extensive text sequences. This capability is further enhanced when paired with LMDeploy, a toolkit designed for compressing, deploying, and serving LLMs. The model demonstrates near-perfect performance in long-context tasks, such as those assessed by LongBench, making it an ideal choice for applications requiring the retrieval of information from large documents1.