GGUF quants for instruction-pretrain/InstructLM-500M using llama.cpp

Quants

• q2_k: Uses Q4_K for the attention.vw and feed_forward.w2 tensors, Q2_K for the other tensors.
• q3_k_s: Uses Q3_K for all tensors
• q3_k_m: Uses Q4_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else Q3_K
• q3_k_l: Uses Q5_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else Q3_K
• q4_0: Original quant method, 4-bit.
• q4_1: Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models.
• q4_k_s: Uses Q4_K for all tensors
• q4_k_m: Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q4_K
• q5_0: Higher accuracy, higher resource usage and slower inference.
• q5_1: Even higher accuracy, resource usage and slower inference.
• q5_k_s: Uses Q5_K for all tensors
• q5_k_m: Uses Q6_K for half of the attention.wv and feed_forward.w2 tensors, else Q5_K
• q6_k: Uses Q8_K for all tensors
• q8_0: Almost indistinguishable from float16. High resource use and slow. Not recommended for most users.