File size: 4,407 Bytes
983070c
 
 
bbc5007
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
983070c
bbc5007
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
983070c
cc24683
983070c
9527171
 
983070c
 
 
f1ff39c
 
 
 
 
 
983070c
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
---
base_model: TransLLaMA/TransLLaMA2-7B-Alpaca
language:
- af
- am
- ar
- hy
- as
- ast
- az
- be
- bn
- bs
- bg
- my
- ca
- ceb
- zho
- hr
- cs
- da
- nl
- en
- et
- tl
- fi
- fr
- ff
- gl
- lg
- ka
- de
- el
- gu
- ha
- he
- hi
- hu
- is
- ig
- id
- ga
- it
- ja
- jv
- kea
- kam
- kn
- kk
- km
- ko
- ky
- lo
- lv
- ln
- lt
- luo
- lb
- mk
- ms
- ml
- mt
- mi
- mr
- mn
- ne
- ns
- no
- ny
- oc
- or
- om
- ps
- fa
- pl
- pt
- pa
- ro
- ru
- sr
- sn
- sd
- sk
- sl
- so
- ku
- es
- sw
- sv
- tg
- ta
- te
- th
- tr
- uk
- umb
- ur
- uz
- vi
- cy
- wo
- xh
- yo
- zu
library_name: transformers
license: mit
quantized_by: mradermacher
tags:
- Multilingual
---
## About

<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type:  -->
<!-- ### tags:  -->
static quants of https://huggingface.co/TransLLaMA/TransLLaMA2-7B-Alpaca

<!-- provided-files -->
weighted/imatrix quants seem not to be available (by me) at this time. If they do not show up a week or so after the static ones, I have probably not planned for them. Feel free to request them by opening a Community Discussion.
## Usage

If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
more details, including on how to concatenate multi-part files.

## Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

| Link | Type | Size/GB | Notes |
|:-----|:-----|--------:|:------|
| [GGUF](https://huggingface.co/mradermacher/TransLLaMA2-7B-Alpaca-GGUF/resolve/main/TransLLaMA2-7B-Alpaca.Q2_K.gguf) | Q2_K | 2.6 |  |
| [GGUF](https://huggingface.co/mradermacher/TransLLaMA2-7B-Alpaca-GGUF/resolve/main/TransLLaMA2-7B-Alpaca.IQ3_XS.gguf) | IQ3_XS | 2.9 |  |
| [GGUF](https://huggingface.co/mradermacher/TransLLaMA2-7B-Alpaca-GGUF/resolve/main/TransLLaMA2-7B-Alpaca.IQ3_S.gguf) | IQ3_S | 3.0 | beats Q3_K* |
| [GGUF](https://huggingface.co/mradermacher/TransLLaMA2-7B-Alpaca-GGUF/resolve/main/TransLLaMA2-7B-Alpaca.Q3_K_S.gguf) | Q3_K_S | 3.0 |  |
| [GGUF](https://huggingface.co/mradermacher/TransLLaMA2-7B-Alpaca-GGUF/resolve/main/TransLLaMA2-7B-Alpaca.IQ3_M.gguf) | IQ3_M | 3.2 |  |
| [GGUF](https://huggingface.co/mradermacher/TransLLaMA2-7B-Alpaca-GGUF/resolve/main/TransLLaMA2-7B-Alpaca.Q3_K_M.gguf) | Q3_K_M | 3.4 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/TransLLaMA2-7B-Alpaca-GGUF/resolve/main/TransLLaMA2-7B-Alpaca.Q3_K_L.gguf) | Q3_K_L | 3.7 |  |
| [GGUF](https://huggingface.co/mradermacher/TransLLaMA2-7B-Alpaca-GGUF/resolve/main/TransLLaMA2-7B-Alpaca.IQ4_XS.gguf) | IQ4_XS | 3.7 |  |
| [GGUF](https://huggingface.co/mradermacher/TransLLaMA2-7B-Alpaca-GGUF/resolve/main/TransLLaMA2-7B-Alpaca.Q4_K_S.gguf) | Q4_K_S | 4.0 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/TransLLaMA2-7B-Alpaca-GGUF/resolve/main/TransLLaMA2-7B-Alpaca.Q4_K_M.gguf) | Q4_K_M | 4.2 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/TransLLaMA2-7B-Alpaca-GGUF/resolve/main/TransLLaMA2-7B-Alpaca.Q5_K_S.gguf) | Q5_K_S | 4.8 |  |
| [GGUF](https://huggingface.co/mradermacher/TransLLaMA2-7B-Alpaca-GGUF/resolve/main/TransLLaMA2-7B-Alpaca.Q5_K_M.gguf) | Q5_K_M | 4.9 |  |
| [GGUF](https://huggingface.co/mradermacher/TransLLaMA2-7B-Alpaca-GGUF/resolve/main/TransLLaMA2-7B-Alpaca.Q6_K.gguf) | Q6_K | 5.6 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/TransLLaMA2-7B-Alpaca-GGUF/resolve/main/TransLLaMA2-7B-Alpaca.Q8_0.gguf) | Q8_0 | 7.3 | fast, best quality |
| [GGUF](https://huggingface.co/mradermacher/TransLLaMA2-7B-Alpaca-GGUF/resolve/main/TransLLaMA2-7B-Alpaca.f16.gguf) | f16 | 13.6 | 16 bpw, overkill |

Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):

![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)

And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

## FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to
questions you might have and/or if you want some other model quantized.

## Thanks

I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.

<!-- end -->