File size: 8,054 Bytes
6074a46
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
5a7e6cc
6074a46
 
 
 
 
60b7b54
8233c10
ddf0787
 
bfa71c4
6074a46
 
 
 
 
60b7b54
8233c10
ed2f8e7
57df8db
ddf0787
4b550be
6074a46
 
ddf0787
1f6d3b5
48bef05
6074a46
 
 
 
bfa71c4
6074a46
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
---
base_model: google/datagemma-rag-27b-it
extra_gated_button_content: Acknowledge license
extra_gated_heading: Access Gemma on Hugging Face
extra_gated_prompt: "To access Gemma on Hugging Face, you\u2019re required to review\
  \ and agree to Google\u2019s usage license. To do this, please ensure you\u2019\
  re logged in to Hugging Face and click below. Requests are processed immediately."
inference: false
library_name: gguf
license: gemma
pipeline_tag: text-generation
quantized_by: legraphista
tags:
- conversational
- quantized
- GGUF
- quantization
- imat
- imatrix
- static
- 8bit
- 6bit
- 5bit
- 4bit
- 3bit
- 2bit
- 1bit
---

# datagemma-rag-27b-it-IMat-GGUF
_Llama.cpp imatrix quantization of google/datagemma-rag-27b-it_

Original Model: [google/datagemma-rag-27b-it](https://huggingface.co/google/datagemma-rag-27b-it)    
Original dtype: `BF16` (`bfloat16`)  
Quantized by:  llama.cpp [b3735](https://github.com/ggerganov/llama.cpp/releases/tag/b3735)  
IMatrix dataset: [here](https://gist.githubusercontent.com/bartowski1182/eb213dccb3571f863da82e99418f81e8/raw/b2869d80f5c16fd7082594248e80144677736635/calibration_datav3.txt)  

- [Files](#files)
    - [IMatrix](#imatrix)
    - [Common Quants](#common-quants)
    - [All Quants](#all-quants)
- [Downloading using huggingface-cli](#downloading-using-huggingface-cli)
- [Inference](#inference)
    - [Simple chat template](#simple-chat-template)
    - [Llama.cpp](#llama-cpp)
- [FAQ](#faq)
    - [Why is the IMatrix not applied everywhere?](#why-is-the-imatrix-not-applied-everywhere)
    - [How do I merge a split GGUF?](#how-do-i-merge-a-split-gguf)

---

## Files

### IMatrix
Status: ✅ Available  
Link: [here](https://huggingface.co/legraphista/datagemma-rag-27b-it-IMat-GGUF/blob/main/imatrix.dat)

### Common Quants
| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
| -------- | ---------- | --------- | ------ | ------------ | -------- |
| [datagemma-rag-27b-it.Q8_0.gguf](https://huggingface.co/legraphista/datagemma-rag-27b-it-IMat-GGUF/blob/main/datagemma-rag-27b-it.Q8_0.gguf) | Q8_0 | 28.94GB | ✅ Available | ⚪ Static | 📦 No
| [datagemma-rag-27b-it.Q6_K.gguf](https://huggingface.co/legraphista/datagemma-rag-27b-it-IMat-GGUF/blob/main/datagemma-rag-27b-it.Q6_K.gguf) | Q6_K | 22.34GB | ✅ Available | ⚪ Static | 📦 No
| [datagemma-rag-27b-it.Q4_K.gguf](https://huggingface.co/legraphista/datagemma-rag-27b-it-IMat-GGUF/blob/main/datagemma-rag-27b-it.Q4_K.gguf) | Q4_K | 16.65GB | ✅ Available | 🟢 IMatrix | 📦 No
| [datagemma-rag-27b-it.Q3_K.gguf](https://huggingface.co/legraphista/datagemma-rag-27b-it-IMat-GGUF/blob/main/datagemma-rag-27b-it.Q3_K.gguf) | Q3_K | 13.42GB | ✅ Available | 🟢 IMatrix | 📦 No
| [datagemma-rag-27b-it.Q2_K.gguf](https://huggingface.co/legraphista/datagemma-rag-27b-it-IMat-GGUF/blob/main/datagemma-rag-27b-it.Q2_K.gguf) | Q2_K | 10.45GB | ✅ Available | 🟢 IMatrix | 📦 No


### All Quants
| Filename | Quant type | File Size | Status | Uses IMatrix | Is Split |
| -------- | ---------- | --------- | ------ | ------------ | -------- |
| [datagemma-rag-27b-it.Q8_0.gguf](https://huggingface.co/legraphista/datagemma-rag-27b-it-IMat-GGUF/blob/main/datagemma-rag-27b-it.Q8_0.gguf) | Q8_0 | 28.94GB | ✅ Available | ⚪ Static | 📦 No
| [datagemma-rag-27b-it.Q6_K.gguf](https://huggingface.co/legraphista/datagemma-rag-27b-it-IMat-GGUF/blob/main/datagemma-rag-27b-it.Q6_K.gguf) | Q6_K | 22.34GB | ✅ Available | ⚪ Static | 📦 No
| [datagemma-rag-27b-it.Q5_K.gguf](https://huggingface.co/legraphista/datagemma-rag-27b-it-IMat-GGUF/blob/main/datagemma-rag-27b-it.Q5_K.gguf) | Q5_K | 19.41GB | ✅ Available | ⚪ Static | 📦 No
| [datagemma-rag-27b-it.Q5_K_S.gguf](https://huggingface.co/legraphista/datagemma-rag-27b-it-IMat-GGUF/blob/main/datagemma-rag-27b-it.Q5_K_S.gguf) | Q5_K_S | 18.88GB | ✅ Available | ⚪ Static | 📦 No
| [datagemma-rag-27b-it.Q4_K.gguf](https://huggingface.co/legraphista/datagemma-rag-27b-it-IMat-GGUF/blob/main/datagemma-rag-27b-it.Q4_K.gguf) | Q4_K | 16.65GB | ✅ Available | 🟢 IMatrix | 📦 No
| [datagemma-rag-27b-it.Q4_K_S.gguf](https://huggingface.co/legraphista/datagemma-rag-27b-it-IMat-GGUF/blob/main/datagemma-rag-27b-it.Q4_K_S.gguf) | Q4_K_S | 15.74GB | ✅ Available | 🟢 IMatrix | 📦 No
| datagemma-rag-27b-it.IQ4_NL | IQ4_NL | - | ⏳ Processing | 🟢 IMatrix | -
| datagemma-rag-27b-it.IQ4_XS | IQ4_XS | - | ⏳ Processing | 🟢 IMatrix | -
| [datagemma-rag-27b-it.Q3_K.gguf](https://huggingface.co/legraphista/datagemma-rag-27b-it-IMat-GGUF/blob/main/datagemma-rag-27b-it.Q3_K.gguf) | Q3_K | 13.42GB | ✅ Available | 🟢 IMatrix | 📦 No
| [datagemma-rag-27b-it.Q3_K_L.gguf](https://huggingface.co/legraphista/datagemma-rag-27b-it-IMat-GGUF/blob/main/datagemma-rag-27b-it.Q3_K_L.gguf) | Q3_K_L | 14.52GB | ✅ Available | 🟢 IMatrix | 📦 No
| [datagemma-rag-27b-it.Q3_K_S.gguf](https://huggingface.co/legraphista/datagemma-rag-27b-it-IMat-GGUF/blob/main/datagemma-rag-27b-it.Q3_K_S.gguf) | Q3_K_S | 12.17GB | ✅ Available | 🟢 IMatrix | 📦 No
| datagemma-rag-27b-it.IQ3_M | IQ3_M | - | ⏳ Processing | 🟢 IMatrix | -
| datagemma-rag-27b-it.IQ3_S | IQ3_S | - | ⏳ Processing | 🟢 IMatrix | -
| datagemma-rag-27b-it.IQ3_XS | IQ3_XS | - | ⏳ Processing | 🟢 IMatrix | -
| datagemma-rag-27b-it.IQ3_XXS | IQ3_XXS | - | ⏳ Processing | 🟢 IMatrix | -
| [datagemma-rag-27b-it.Q2_K.gguf](https://huggingface.co/legraphista/datagemma-rag-27b-it-IMat-GGUF/blob/main/datagemma-rag-27b-it.Q2_K.gguf) | Q2_K | 10.45GB | ✅ Available | 🟢 IMatrix | 📦 No
| datagemma-rag-27b-it.Q2_K_S | Q2_K_S | - | ⏳ Processing | 🟢 IMatrix | -
| datagemma-rag-27b-it.IQ2_M | IQ2_M | - | ⏳ Processing | 🟢 IMatrix | -
| datagemma-rag-27b-it.IQ2_S | IQ2_S | - | ⏳ Processing | 🟢 IMatrix | -
| datagemma-rag-27b-it.IQ2_XS | IQ2_XS | - | ⏳ Processing | 🟢 IMatrix | -
| datagemma-rag-27b-it.IQ2_XXS | IQ2_XXS | - | ⏳ Processing | 🟢 IMatrix | -
| datagemma-rag-27b-it.IQ1_M | IQ1_M | - | ⏳ Processing | 🟢 IMatrix | -
| datagemma-rag-27b-it.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/datagemma-rag-27b-it-IMat-GGUF --include "datagemma-rag-27b-it.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/datagemma-rag-27b-it-IMat-GGUF --include "datagemma-rag-27b-it.Q8_0/*" --local-dir ./
# see FAQ for merging GGUF's
```

---

## Inference

### Simple chat template
```
<bos><start_of_turn>user
{user_prompt}<end_of_turn>
<start_of_turn>model
{assistant_response}<end_of_turn>
<start_of_turn>user
{next_user_prompt}<end_of_turn>

```

### Llama.cpp
```
llama.cpp/main -m datagemma-rag-27b-it.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](https://www.reddit.com/r/LocalLLaMA/comments/1993iro/ggufs_quants_can_punch_above_their_weights_now/), 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
    - To get hold of `gguf-split`, navigate to https://github.com/ggerganov/llama.cpp/releases
    - Download the appropriate zip for your system from the latest release
    - Unzip the archive and you should be able to find `gguf-split`
2. Locate your GGUF chunks folder (ex: `datagemma-rag-27b-it.Q8_0`)
3. Run `gguf-split --merge datagemma-rag-27b-it.Q8_0/datagemma-rag-27b-it.Q8_0-00001-of-XXXXX.gguf datagemma-rag-27b-it.Q8_0.gguf`
    - Make sure to point `gguf-split` to the first chunk of the split.

---

Got a suggestion? Ping me [@legraphista](https://x.com/legraphista)!