Original model: https://huggingface.co/FuseAI/FuseChat-Llama-3.2-1B-Instruct Some of these quants (Q3KXL, Q4KL etc) are the standard quantization method with the embeddings and output weights quantized to Q8_0 instead of what they would normally default to. If the model is bigger than 50GB, it will have been split into multiple files. In order to download them all to a local folder, run: You can either specify a new local-dir (FuseChat-Llama-3.2-1B-Instruct-Q8_0) or download them all in place (./) New: Thanks to efforts made to have online repacking of weights in this PR, you can now just use Q4_0 if your llama.cpp has been compiled for your ARM device. Similarly, if you want to get slightly better performance, you can use IQ4NL thanks to this PR which will also repack the weights for ARM, though only the 44 for now. The loading time may be slower but it will result in an overall speed incrase. Click to view Q40XX information These are NOT* for Metal (Apple) or GPU (nvidia/AMD/intel) offloading, only ARM chips (and certain AVX2/AVX512 CPUs). If you’re using an ARM chip, the Q40XX quants will have a substantial speedup. Check out Q4044 speed comparisons on the original pull request…
Модальности:
Генерация текста
Области применения:
Диалог / чат Следование инструкциям
Задача: Генерация текста
Автор: bartowski
Теги: gguf, endpoints_compatible, imatrix, conversational
Лайков: 4 | Загрузок: 721
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
