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LLaMA-30B-ggml

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Duplicate from localmodels/LLM

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  1. .gitattributes +34 -0
  2. README.md +36 -0
  3. llama-30b.ggmlv3.q2_K.bin +3 -0
  4. llama-30b.ggmlv3.q3_K_L.bin +3 -0
  5. llama-30b.ggmlv3.q3_K_M.bin +3 -0
  6. llama-30b.ggmlv3.q3_K_S.bin +3 -0
  7. llama-30b.ggmlv3.q4_0.bin +3 -0
  8. llama-30b.ggmlv3.q4_1.bin +3 -0
  9. llama-30b.ggmlv3.q4_K_M.bin +3 -0
  10. llama-30b.ggmlv3.q4_K_S.bin +3 -0
  11. llama-30b.ggmlv3.q5_0.bin +3 -0
  12. llama-30b.ggmlv3.q5_1.bin +3 -0
  13. llama-30b.ggmlv3.q5_K_M.bin +3 -0
  14. llama-30b.ggmlv3.q5_K_S.bin +3 -0
  15. llama-30b.ggmlv3.q6_K.bin +3 -0
  16. llama-30b.ggmlv3.q8_0.bin +3 -0
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README.md ADDED
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+ ---
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+ duplicated_from: localmodels/LLM
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+ ---
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+ # LLaMA 30B ggml
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+
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+ From Meta: https://ai.meta.com/blog/large-language-model-llama-meta-ai
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+
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+ ---
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+
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+ ### Original llama.cpp quant methods: `q4_0, q4_1, q5_0, q5_1, q8_0`
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+
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+ Quantized using an older version of llama.cpp and compatible with llama.cpp from May 19, commit 2d5db48.
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+
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+ ### k-quant methods: `q2_K, q3_K_S, q3_K_M, q3_K_L, q4_K_S, q4_K_M, q5_K_S, q6_K`
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+
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+ Quantization methods compatible with latest llama.cpp from June 6, commit 2d43387.
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+
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+ ---
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+
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+ ## Provided files
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+ | Name | Quant method | Bits | Size | Max RAM required | Use case |
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+ | ---- | ---- | ---- | ---- | ---- | ----- |
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+ | llama-30b.ggmlv3.q2_K.bin | q2_K | 2 | 13.60 GB| 16.10 GB | New k-quant method. Uses GGML_TYPE_Q4_K for the attention.vw and feed_forward.w2 tensors, GGML_TYPE_Q2_K for the other tensors. |
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+ | llama-30b.ggmlv3.q3_K_L.bin | q3_K_L | 3 | 17.20 GB| 19.70 GB | New k-quant method. Uses GGML_TYPE_Q5_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else GGML_TYPE_Q3_K |
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+ | llama-30b.ggmlv3.q3_K_M.bin | q3_K_M | 3 | 15.64 GB| 18.14 GB | New k-quant method. Uses GGML_TYPE_Q4_K for the attention.wv, attention.wo, and feed_forward.w2 tensors, else GGML_TYPE_Q3_K |
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+ | llama-30b.ggmlv3.q3_K_S.bin | q3_K_S | 3 | 13.98 GB| 16.48 GB | New k-quant method. Uses GGML_TYPE_Q3_K for all tensors |
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+ | llama-30b.ggmlv3.q4_0.bin | q4_0 | 4 | 18.30 GB| 20.80 GB | Original quant method, 4-bit. |
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+ | llama-30b.ggmlv3.q4_1.bin | q4_1 | 4 | 20.33 GB| 22.83 GB | Original quant method, 4-bit. Higher accuracy than q4_0 but not as high as q5_0. However has quicker inference than q5 models. |
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+ | llama-30b.ggmlv3.q4_K_M.bin | q4_K_M | 4 | 19.57 GB| 22.07 GB | New k-quant method. Uses GGML_TYPE_Q6_K for half of the attention.wv and feed_forward.w2 tensors, else GGML_TYPE_Q4_K |
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+ | llama-30b.ggmlv3.q4_K_S.bin | q4_K_S | 4 | 18.30 GB| 20.80 GB | New k-quant method. Uses GGML_TYPE_Q4_K for all tensors |
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+ | llama-30b.ggmlv3.q5_0.bin | q5_0 | 5 | 22.37 GB| 24.87 GB | Original quant method, 5-bit. Higher accuracy, higher resource usage and slower inference. |
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+ | llama-30b.ggmlv3.q5_1.bin | q5_1 | 5 | 24.40 GB| 26.90 GB | Original quant method, 5-bit. Even higher accuracy, resource usage and slower inference. |
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+ | llama-30b.ggmlv3.q5_K_M.bin | q5_K_M | 5 | 23.02 GB| 25.52 GB | New k-quant method. Uses GGML_TYPE_Q6_K for half of the attention.wv and feed_forward.w2 tensors, else GGML_TYPE_Q5_K |
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+ | llama-30b.ggmlv3.q5_K_S.bin | q5_K_S | 5 | 22.37 GB| 24.87 GB | New k-quant method. Uses GGML_TYPE_Q5_K for all tensors |
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+ | llama-30b.ggmlv3.q6_K.bin | q6_K | 6 | 26.69 GB| 29.19 GB | New k-quant method. Uses GGML_TYPE_Q8_K for all tensors - 6-bit quantization |
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+ | llama-30b.ggmlv3.q8_0.bin | q8_0 | 8 | 34.56 GB| 37.06 GB | Original quant method, 8-bit. Almost indistinguishable from float16. High resource use and slow. Not recommended for most users. |
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