K2-IMat-GGUF / README.md
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metadata
base_model: LLM360/K2
inference: false
language:
  - en
library_name: gguf
license: apache-2.0
pipeline_tag: text-generation
quantized_by: legraphista
tags:
  - nlp
  - llm
  - quantized
  - GGUF
  - imatrix
  - quantization
  - imat
  - imatrix
  - static
  - 16bit
  - 8bit
  - 6bit
  - 5bit
  - 4bit
  - 3bit
  - 2bit
  - 1bit

K2-IMat-GGUF

Llama.cpp imatrix quantization of LLM360/K2

Original Model: LLM360/K2
Original dtype: FP16 (float16)
Quantized by: llama.cpp b3051
IMatrix dataset: here


Files

IMatrix

Status: βœ… Available
Link: here

Common Quants

Filename Quant type File Size Status Uses IMatrix Is Split
K2.Q8_0/* Q8_0 69.37GB βœ… Available βšͺ Static βœ‚ Yes
K2.Q6_K/* Q6_K 53.56GB βœ… Available βšͺ Static βœ‚ Yes
K2.Q4_K.gguf Q4_K 39.35GB βœ… Available 🟒 IMatrix πŸ“¦ No
K2.Q3_K.gguf Q3_K 31.63GB βœ… Available 🟒 IMatrix πŸ“¦ No
K2.Q2_K.gguf Q2_K 24.11GB βœ… Available 🟒 IMatrix πŸ“¦ No

All Quants

Filename Quant type File Size Status Uses IMatrix Is Split
K2.FP16/* F16 130.58GB βœ… Available βšͺ Static βœ‚ Yes
K2.Q8_0/* Q8_0 69.37GB βœ… Available βšͺ Static βœ‚ Yes
K2.Q6_K/* Q6_K 53.56GB βœ… Available βšͺ Static βœ‚ Yes
K2.Q5_K/* Q5_K 46.24GB βœ… Available βšͺ Static βœ‚ Yes
K2.Q5_K_S.gguf Q5_K_S 44.92GB βœ… Available βšͺ Static πŸ“¦ No
K2.Q4_K.gguf Q4_K 39.35GB βœ… Available 🟒 IMatrix πŸ“¦ No
K2.Q4_K_S.gguf Q4_K_S 37.06GB βœ… Available 🟒 IMatrix πŸ“¦ No
K2.IQ4_NL IQ4_NL - ⏳ Processing 🟒 IMatrix -
K2.IQ4_XS IQ4_XS - ⏳ Processing 🟒 IMatrix -
K2.Q3_K.gguf Q3_K 31.63GB βœ… Available 🟒 IMatrix πŸ“¦ No
K2.Q3_K_L Q3_K_L - ⏳ Processing 🟒 IMatrix -
K2.Q3_K_S Q3_K_S - ⏳ Processing 🟒 IMatrix -
K2.IQ3_M IQ3_M - ⏳ Processing 🟒 IMatrix -
K2.IQ3_S IQ3_S - ⏳ Processing 🟒 IMatrix -
K2.IQ3_XS IQ3_XS - ⏳ Processing 🟒 IMatrix -
K2.IQ3_XXS IQ3_XXS - ⏳ Processing 🟒 IMatrix -
K2.Q2_K.gguf Q2_K 24.11GB βœ… Available 🟒 IMatrix πŸ“¦ No
K2.Q2_K_S Q2_K_S - ⏳ Processing 🟒 IMatrix -
K2.IQ2_M IQ2_M - ⏳ Processing 🟒 IMatrix -
K2.IQ2_S IQ2_S - ⏳ Processing 🟒 IMatrix -
K2.IQ2_XS IQ2_XS - ⏳ Processing 🟒 IMatrix -
K2.IQ2_XXS IQ2_XXS - ⏳ Processing 🟒 IMatrix -
K2.IQ1_M IQ1_M - ⏳ Processing 🟒 IMatrix -
K2.IQ1_S IQ1_S - ⏳ Processing 🟒 IMatrix -

Downloading using huggingface-cli

If you do not have hugginface-cli installed:

pip install -U "huggingface_hub[cli]"

Download the specific file you want:

huggingface-cli download legraphista/K2-IMat-GGUF --include "K2.Q8_0.gguf" --local-dir ./

If the model file is big, it has been split into multiple files. In order to download them all to a local folder, run:

huggingface-cli download legraphista/K2-IMat-GGUF --include "K2.Q8_0/*" --local-dir ./
# see FAQ for merging GGUF's

Inference

Llama.cpp

llama.cpp/main -m K2.Q8_0.gguf --color -i -p "prompt here"

FAQ

Why is the IMatrix not applied everywhere?

According to this investigation, it appears that lower quantizations are the only ones that benefit from the imatrix input (as per hellaswag results).

How do I merge a split GGUF?

  1. Make sure you have gguf-split available
  2. Locate your GGUF chunks folder (ex: K2.Q8_0)
  3. Run gguf-split --merge K2.Q8_0/K2.Q8_0-00001-of-XXXXX.gguf K2.Q8_0.gguf
    • Make sure to point gguf-split to the first chunk of the split.

Got a suggestion? Ping me @legraphista!