Hugging Face's logo

mradermacher
/
Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF

Transformers
GGUF
English
Korean
Spanish
lg-ai
exaone
exaone-4.0
abliterated
uncensored
imatrix
conversational
Model card Files
xet
Community
mradermacher commited on
Commit
292a2cf
·
verified ·
1 Parent(s): 14b1bf7

auto-patch README.md

Browse files
Files changed (1) hide show
  1. README.md +85 -0
README.md CHANGED
@@ -1,6 +1,91 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  <!-- ### quantize_version: 2 -->
2
  <!-- ### output_tensor_quantised: 1 -->
3
  <!-- ### convert_type: hf -->
4
  <!-- ### vocab_type: -->
5
  <!-- ### tags: nicoboss -->
6
  weighted/imatrix quants of https://huggingface.co/huihui-ai/Huihui-EXAONE-4.0-1.2B-abliterated
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: huihui-ai/Huihui-EXAONE-4.0-1.2B-abliterated
3
+ language:
4
+ - en
5
+ - ko
6
+ - es
7
+ library_name: transformers
8
+ license: other
9
+ license_link: LICENSE
10
+ license_name: exaone
11
+ mradermacher:
12
+ readme_rev: 1
13
+ quantized_by: mradermacher
14
+ tags:
15
+ - lg-ai
16
+ - exaone
17
+ - exaone-4.0
18
+ - abliterated
19
+ - uncensored
20
+ ---
21
+ ## About
22
+
23
  <!-- ### quantize_version: 2 -->
24
  <!-- ### output_tensor_quantised: 1 -->
25
  <!-- ### convert_type: hf -->
26
  <!-- ### vocab_type: -->
27
  <!-- ### tags: nicoboss -->
28
  weighted/imatrix quants of https://huggingface.co/huihui-ai/Huihui-EXAONE-4.0-1.2B-abliterated
29
+
30
+ <!-- provided-files -->
31
+
32
+ ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF).***
33
+
34
+ static quants are available at https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-GGUF
35
+ ## Usage
36
+
37
+ If you are unsure how to use GGUF files, refer to one of [TheBloke's
38
+ READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
39
+ more details, including on how to concatenate multi-part files.
40
+
41
+ ## Provided Quants
42
+
43
+ (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
44
+
45
+ | Link | Type | Size/GB | Notes |
46
+ |:-----|:-----|--------:|:------|
47
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-IQ1_S.gguf) | i1-IQ1_S | 0.5 | for the desperate |
48
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-IQ1_M.gguf) | i1-IQ1_M | 0.5 | mostly desperate |
49
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-IQ2_XXS.gguf) | i1-IQ2_XXS | 0.5 | |
50
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-IQ2_XS.gguf) | i1-IQ2_XS | 0.6 | |
51
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-IQ2_S.gguf) | i1-IQ2_S | 0.6 | |
52
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-IQ2_M.gguf) | i1-IQ2_M | 0.6 | |
53
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-Q2_K_S.gguf) | i1-Q2_K_S | 0.6 | very low quality |
54
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-IQ3_XXS.gguf) | i1-IQ3_XXS | 0.7 | lower quality |
55
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-Q2_K.gguf) | i1-Q2_K | 0.7 | IQ3_XXS probably better |
56
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-IQ3_XS.gguf) | i1-IQ3_XS | 0.7 | |
57
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-Q3_K_S.gguf) | i1-Q3_K_S | 0.7 | IQ3_XS probably better |
58
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-IQ3_S.gguf) | i1-IQ3_S | 0.7 | beats Q3_K* |
59
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-IQ3_M.gguf) | i1-IQ3_M | 0.8 | |
60
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-Q3_K_M.gguf) | i1-Q3_K_M | 0.8 | IQ3_S probably better |
61
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-Q3_K_L.gguf) | i1-Q3_K_L | 0.8 | IQ3_M probably better |
62
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-IQ4_XS.gguf) | i1-IQ4_XS | 0.8 | |
63
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-Q4_0.gguf) | i1-Q4_0 | 0.9 | fast, low quality |
64
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-Q4_K_S.gguf) | i1-Q4_K_S | 0.9 | optimal size/speed/quality |
65
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-IQ4_NL.gguf) | i1-IQ4_NL | 0.9 | prefer IQ4_XS |
66
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-Q4_K_M.gguf) | i1-Q4_K_M | 0.9 | fast, recommended |
67
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-Q4_1.gguf) | i1-Q4_1 | 0.9 | |
68
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-Q5_K_S.gguf) | i1-Q5_K_S | 1.0 | |
69
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-Q5_K_M.gguf) | i1-Q5_K_M | 1.0 | |
70
+ | [GGUF](https://huggingface.co/mradermacher/Huihui-EXAONE-4.0-1.2B-abliterated-i1-GGUF/resolve/main/Huihui-EXAONE-4.0-1.2B-abliterated.i1-Q6_K.gguf) | i1-Q6_K | 1.2 | practically like static Q6_K |
71
+
72
+ Here is a handy graph by ikawrakow comparing some lower-quality quant
73
+ types (lower is better):
74
+
75
+ ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
76
+
77
+ And here are Artefact2's thoughts on the matter:
78
+ https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
79
+
80
+ ## FAQ / Model Request
81
+
82
+ See https://huggingface.co/mradermacher/model_requests for some answers to
83
+ questions you might have and/or if you want some other model quantized.
84
+
85
+ ## Thanks
86
+
87
+ I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
88
+ me use its servers and providing upgrades to my workstation to enable
89
+ this work in my free time. Additional thanks to [@nicoboss](https://huggingface.co/nicoboss) for giving me access to his private supercomputer, enabling me to provide many more imatrix quants, at much higher quality, than I would otherwise be able to.
90
+
91
+ <!-- end -->