Edit model card

shieldgemma-9b-IMat-GGUF

Llama.cpp imatrix quantization of google/shieldgemma-9b

Original Model: google/shieldgemma-9b
Original dtype: BF16 (bfloat16)
Quantized by: llama.cpp b3525
IMatrix dataset: here


Files

IMatrix

Status: ✅ Available
Link: here

Common Quants

Filename Quant type File Size Status Uses IMatrix Is Split
shieldgemma-9b.Q8_0.gguf Q8_0 9.83GB ✅ Available ⚪ Static 📦 No
shieldgemma-9b.Q6_K.gguf Q6_K 7.59GB ✅ Available ⚪ Static 📦 No
shieldgemma-9b.Q4_K.gguf Q4_K 5.76GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.Q3_K.gguf Q3_K 4.76GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.Q2_K.gguf Q2_K 3.81GB ✅ Available 🟢 IMatrix 📦 No

All Quants

Filename Quant type File Size Status Uses IMatrix Is Split
shieldgemma-9b.BF16.gguf BF16 18.49GB ✅ Available ⚪ Static 📦 No
shieldgemma-9b.FP16.gguf F16 18.49GB ✅ Available ⚪ Static 📦 No
shieldgemma-9b.Q8_0.gguf Q8_0 9.83GB ✅ Available ⚪ Static 📦 No
shieldgemma-9b.Q6_K.gguf Q6_K 7.59GB ✅ Available ⚪ Static 📦 No
shieldgemma-9b.Q5_K.gguf Q5_K 6.65GB ✅ Available ⚪ Static 📦 No
shieldgemma-9b.Q5_K_S.gguf Q5_K_S 6.48GB ✅ Available ⚪ Static 📦 No
shieldgemma-9b.Q4_K.gguf Q4_K 5.76GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.Q4_K_S.gguf Q4_K_S 5.48GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.IQ4_NL.gguf IQ4_NL 5.44GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.IQ4_XS.gguf IQ4_XS 5.18GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.Q3_K.gguf Q3_K 4.76GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.Q3_K_L.gguf Q3_K_L 5.13GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.Q3_K_S.gguf Q3_K_S 4.34GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.IQ3_M.gguf IQ3_M 4.49GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.IQ3_S.gguf IQ3_S 4.34GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.IQ3_XS.gguf IQ3_XS 4.14GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.IQ3_XXS.gguf IQ3_XXS 3.80GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.Q2_K.gguf Q2_K 3.81GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.Q2_K_S.gguf Q2_K_S 3.55GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.IQ2_M.gguf IQ2_M 3.43GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.IQ2_S.gguf IQ2_S 3.21GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.IQ2_XS.gguf IQ2_XS 3.07GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.IQ2_XXS.gguf IQ2_XXS 2.82GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.IQ1_M.gguf IQ1_M 2.55GB ✅ Available 🟢 IMatrix 📦 No
shieldgemma-9b.IQ1_S.gguf IQ1_S 2.38GB ✅ Available 🟢 IMatrix 📦 No

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/shieldgemma-9b-IMat-GGUF --include "shieldgemma-9b.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/shieldgemma-9b-IMat-GGUF --include "shieldgemma-9b.Q8_0/*" --local-dir ./
# see FAQ for merging GGUF's

Inference

Simple chat template

<bos>You are a policy expert trying to help determine whether a user prompt is in violation of the defined safety policies.

<start_of_turn>
Human Question: {next_user_prompt}
<end_of_turn>

Our safety principle is defined in the below:

* {guideline}

===

Does the human question violate the above principle? Your answer must start with 'Yes' or 'No'. And then walk through step by step to be sure we answer correctly.

Llama.cpp

llama.cpp/main -m shieldgemma-9b.Q8_0.gguf --color -i -p "prompt here (according to the chat template)"

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: shieldgemma-9b.Q8_0)
  3. Run gguf-split --merge shieldgemma-9b.Q8_0/shieldgemma-9b.Q8_0-00001-of-XXXXX.gguf shieldgemma-9b.Q8_0.gguf
    • Make sure to point gguf-split to the first chunk of the split.

Got a suggestion? Ping me @legraphista!

Downloads last month
481
GGUF
Model size
9.24B params
Architecture
gemma2

1-bit

2-bit

3-bit

4-bit

5-bit

6-bit

8-bit

16-bit

Inference Examples
Inference API (serverless) has been turned off for this model.

Model tree for legraphista/shieldgemma-9b-IMat-GGUF

Quantized
(10)
this model

Collection including legraphista/shieldgemma-9b-IMat-GGUF