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So far I've ported the following models to Java:
Llama 3 & 3.1, Mistral/Codestral/Mathstral/Nemostral (+ Tekken tokenizer), Qwen2, Phi3 and Gemma 1 & 2 ...
All models are bundled as a single ~2K lines Java file with no dependencies, at this point, maintaining all these is a burden, some components can be shared e.g. GGUF parser, tensors, tokenizers, samplers, chat formats, even the inference (e.g. same for Mistral and Llama), would be great to have all of them as a single project.
All behind a common, low-level inference API e.g. forward implementation. Note that this is not meant high-level abstraction like langchain4j, but a low-level inference engine that can be used as a backend by langchain4j.
The text was updated successfully, but these errors were encountered:
So far I've ported the following models to Java:
Llama 3 & 3.1, Mistral/Codestral/Mathstral/Nemostral (+ Tekken tokenizer), Qwen2, Phi3 and Gemma 1 & 2 ...
All models are bundled as a single ~2K lines Java file with no dependencies, at this point, maintaining all these is a burden, some components can be shared e.g. GGUF parser, tensors, tokenizers, samplers, chat formats, even the inference (e.g. same for Mistral and Llama), would be great to have all of them as a single project.
All behind a common, low-level inference API e.g. forward implementation. Note that this is not meant high-level abstraction like langchain4j, but a low-level inference engine that can be used as a backend by langchain4j.
The text was updated successfully, but these errors were encountered: