mradermacher commited on
Commit
7cac3ca
1 Parent(s): 4deee9f

auto-patch README.md

Browse files
Files changed (1) hide show
  1. README.md +65 -0
README.md CHANGED
@@ -1,6 +1,71 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  <!-- ### quantize_version: 2 -->
2
  <!-- ### output_tensor_quantised: 1 -->
3
  <!-- ### convert_type: hf -->
4
  <!-- ### vocab_type: -->
5
  <!-- ### tags: nicoboss -->
6
  static quants of https://huggingface.co/Eric111/Mayo
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: Eric111/Mayo
3
+ language:
4
+ - en
5
+ library_name: transformers
6
+ license: apache-2.0
7
+ quantized_by: mradermacher
8
+ tags:
9
+ - merge
10
+ - mergekit
11
+ - lazymergekit
12
+ - mlabonne/NeuralBeagle14-7B
13
+ - openchat/openchat-3.5-0106
14
+ ---
15
+ ## About
16
+
17
  <!-- ### quantize_version: 2 -->
18
  <!-- ### output_tensor_quantised: 1 -->
19
  <!-- ### convert_type: hf -->
20
  <!-- ### vocab_type: -->
21
  <!-- ### tags: nicoboss -->
22
  static quants of https://huggingface.co/Eric111/Mayo
23
+
24
+ <!-- provided-files -->
25
+ 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.
26
+ ## Usage
27
+
28
+ If you are unsure how to use GGUF files, refer to one of [TheBloke's
29
+ READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
30
+ more details, including on how to concatenate multi-part files.
31
+
32
+ ## Provided Quants
33
+
34
+ (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
35
+
36
+ | Link | Type | Size/GB | Notes |
37
+ |:-----|:-----|--------:|:------|
38
+ | [GGUF](https://huggingface.co/mradermacher/Mayo-GGUF/resolve/main/Mayo.Q2_K.gguf) | Q2_K | 2.8 | |
39
+ | [GGUF](https://huggingface.co/mradermacher/Mayo-GGUF/resolve/main/Mayo.Q3_K_S.gguf) | Q3_K_S | 3.3 | |
40
+ | [GGUF](https://huggingface.co/mradermacher/Mayo-GGUF/resolve/main/Mayo.Q3_K_M.gguf) | Q3_K_M | 3.6 | lower quality |
41
+ | [GGUF](https://huggingface.co/mradermacher/Mayo-GGUF/resolve/main/Mayo.Q3_K_L.gguf) | Q3_K_L | 3.9 | |
42
+ | [GGUF](https://huggingface.co/mradermacher/Mayo-GGUF/resolve/main/Mayo.IQ4_XS.gguf) | IQ4_XS | 4.0 | |
43
+ | [GGUF](https://huggingface.co/mradermacher/Mayo-GGUF/resolve/main/Mayo.Q4_0_4_4.gguf) | Q4_0_4_4 | 4.2 | fast on arm, low quality |
44
+ | [GGUF](https://huggingface.co/mradermacher/Mayo-GGUF/resolve/main/Mayo.Q4_K_S.gguf) | Q4_K_S | 4.2 | fast, recommended |
45
+ | [GGUF](https://huggingface.co/mradermacher/Mayo-GGUF/resolve/main/Mayo.Q4_K_M.gguf) | Q4_K_M | 4.5 | fast, recommended |
46
+ | [GGUF](https://huggingface.co/mradermacher/Mayo-GGUF/resolve/main/Mayo.Q5_K_S.gguf) | Q5_K_S | 5.1 | |
47
+ | [GGUF](https://huggingface.co/mradermacher/Mayo-GGUF/resolve/main/Mayo.Q5_K_M.gguf) | Q5_K_M | 5.2 | |
48
+ | [GGUF](https://huggingface.co/mradermacher/Mayo-GGUF/resolve/main/Mayo.Q6_K.gguf) | Q6_K | 6.0 | very good quality |
49
+ | [GGUF](https://huggingface.co/mradermacher/Mayo-GGUF/resolve/main/Mayo.Q8_0.gguf) | Q8_0 | 7.8 | fast, best quality |
50
+ | [GGUF](https://huggingface.co/mradermacher/Mayo-GGUF/resolve/main/Mayo.f16.gguf) | f16 | 14.6 | 16 bpw, overkill |
51
+
52
+ Here is a handy graph by ikawrakow comparing some lower-quality quant
53
+ types (lower is better):
54
+
55
+ ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
56
+
57
+ And here are Artefact2's thoughts on the matter:
58
+ https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
59
+
60
+ ## FAQ / Model Request
61
+
62
+ See https://huggingface.co/mradermacher/model_requests for some answers to
63
+ questions you might have and/or if you want some other model quantized.
64
+
65
+ ## Thanks
66
+
67
+ I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
68
+ me use its servers and providing upgrades to my workstation to enable
69
+ 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.
70
+
71
+ <!-- end -->