LLM: tips untuk CPU: Difference between revisions
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Created page with "Kata CGPT: saat pake CPU, coba: 1. Batch Processing u. kurangi overhead & speedup embedding. 2. Kurangi presisi model; float32->float16/int8; speedup tanpa korbankan akuras..." |
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4. Multi-threading. | 4. Multi-threading. | ||
5. Gunakan Intel MKL / OpenBLAS. | 5. Gunakan Intel MKL / OpenBLAS. | ||
saya pakai model intfloat pak, lumayan cepet di CPU https://huggingface.co/intfloat/multilingual-e5-large | |||
kalo pdf bisanya saya parse dulu textnya atau pakai ocr, terus embeddingnya disimpan di postgre pakai pgvector (https://github.com/pgvector/pgvector) | |||
agak effort sih | |||
Latest revision as of 21:26, 16 July 2024
Kata CGPT: saat pake CPU, coba:
1. Batch Processing u. kurangi overhead & speedup embedding. 2. Kurangi presisi model; float32->float16/int8; speedup tanpa korbankan akurasi. 3. Buat versi kecil dari model yg sama. 4. Multi-threading. 5. Gunakan Intel MKL / OpenBLAS.
saya pakai model intfloat pak, lumayan cepet di CPU https://huggingface.co/intfloat/multilingual-e5-large
kalo pdf bisanya saya parse dulu textnya atau pakai ocr, terus embeddingnya disimpan di postgre pakai pgvector (https://github.com/pgvector/pgvector) agak effort sih
