Transformers
GGUF
English
Chinese
Inference Endpoints
mradermacher commited on
Commit
de79c6d
1 Parent(s): f4b155b

auto-patch README.md

Browse files
Files changed (1) hide show
  1. README.md +66 -0
README.md CHANGED
@@ -1,6 +1,72 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  <!-- ### quantize_version: 2 -->
2
  <!-- ### output_tensor_quantised: 1 -->
3
  <!-- ### convert_type: hf -->
4
  <!-- ### vocab_type: -->
5
  <!-- ### tags: -->
6
  static quants of https://huggingface.co/GeneZC/MiniMA-2-1B
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: GeneZC/MiniMA-2-1B
3
+ datasets:
4
+ - EleutherAI/pile
5
+ - togethercomputer/RedPajama-Data-1T
6
+ - p208p2002/wudao
7
+ language:
8
+ - en
9
+ - zh
10
+ library_name: transformers
11
+ license: apache-2.0
12
+ quantized_by: mradermacher
13
+ ---
14
+ ## About
15
+
16
  <!-- ### quantize_version: 2 -->
17
  <!-- ### output_tensor_quantised: 1 -->
18
  <!-- ### convert_type: hf -->
19
  <!-- ### vocab_type: -->
20
  <!-- ### tags: -->
21
  static quants of https://huggingface.co/GeneZC/MiniMA-2-1B
22
+
23
+ <!-- provided-files -->
24
+ 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.
25
+ ## Usage
26
+
27
+ If you are unsure how to use GGUF files, refer to one of [TheBloke's
28
+ READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
29
+ more details, including on how to concatenate multi-part files.
30
+
31
+ ## Provided Quants
32
+
33
+ (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
34
+
35
+ | Link | Type | Size/GB | Notes |
36
+ |:-----|:-----|--------:|:------|
37
+ | [GGUF](https://huggingface.co/mradermacher/MiniMA-2-1B-GGUF/resolve/main/MiniMA-2-1B.Q2_K.gguf) | Q2_K | 0.7 | |
38
+ | [GGUF](https://huggingface.co/mradermacher/MiniMA-2-1B-GGUF/resolve/main/MiniMA-2-1B.IQ3_XS.gguf) | IQ3_XS | 0.7 | |
39
+ | [GGUF](https://huggingface.co/mradermacher/MiniMA-2-1B-GGUF/resolve/main/MiniMA-2-1B.IQ3_S.gguf) | IQ3_S | 0.7 | beats Q3_K* |
40
+ | [GGUF](https://huggingface.co/mradermacher/MiniMA-2-1B-GGUF/resolve/main/MiniMA-2-1B.Q3_K_S.gguf) | Q3_K_S | 0.7 | |
41
+ | [GGUF](https://huggingface.co/mradermacher/MiniMA-2-1B-GGUF/resolve/main/MiniMA-2-1B.IQ3_M.gguf) | IQ3_M | 0.8 | |
42
+ | [GGUF](https://huggingface.co/mradermacher/MiniMA-2-1B-GGUF/resolve/main/MiniMA-2-1B.Q3_K_M.gguf) | Q3_K_M | 0.8 | lower quality |
43
+ | [GGUF](https://huggingface.co/mradermacher/MiniMA-2-1B-GGUF/resolve/main/MiniMA-2-1B.Q3_K_L.gguf) | Q3_K_L | 0.9 | |
44
+ | [GGUF](https://huggingface.co/mradermacher/MiniMA-2-1B-GGUF/resolve/main/MiniMA-2-1B.IQ4_XS.gguf) | IQ4_XS | 0.9 | |
45
+ | [GGUF](https://huggingface.co/mradermacher/MiniMA-2-1B-GGUF/resolve/main/MiniMA-2-1B.Q4_K_S.gguf) | Q4_K_S | 0.9 | fast, recommended |
46
+ | [GGUF](https://huggingface.co/mradermacher/MiniMA-2-1B-GGUF/resolve/main/MiniMA-2-1B.Q4_K_M.gguf) | Q4_K_M | 0.9 | fast, recommended |
47
+ | [GGUF](https://huggingface.co/mradermacher/MiniMA-2-1B-GGUF/resolve/main/MiniMA-2-1B.Q5_K_S.gguf) | Q5_K_S | 1.1 | |
48
+ | [GGUF](https://huggingface.co/mradermacher/MiniMA-2-1B-GGUF/resolve/main/MiniMA-2-1B.Q5_K_M.gguf) | Q5_K_M | 1.1 | |
49
+ | [GGUF](https://huggingface.co/mradermacher/MiniMA-2-1B-GGUF/resolve/main/MiniMA-2-1B.Q6_K.gguf) | Q6_K | 1.2 | very good quality |
50
+ | [GGUF](https://huggingface.co/mradermacher/MiniMA-2-1B-GGUF/resolve/main/MiniMA-2-1B.Q8_0.gguf) | Q8_0 | 1.6 | fast, best quality |
51
+ | [GGUF](https://huggingface.co/mradermacher/MiniMA-2-1B-GGUF/resolve/main/MiniMA-2-1B.f16.gguf) | f16 | 2.8 | 16 bpw, overkill |
52
+
53
+ Here is a handy graph by ikawrakow comparing some lower-quality quant
54
+ types (lower is better):
55
+
56
+ ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
57
+
58
+ And here are Artefact2's thoughts on the matter:
59
+ https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
60
+
61
+ ## FAQ / Model Request
62
+
63
+ See https://huggingface.co/mradermacher/model_requests for some answers to
64
+ questions you might have and/or if you want some other model quantized.
65
+
66
+ ## Thanks
67
+
68
+ I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
69
+ me use its servers and providing upgrades to my workstation to enable
70
+ this work in my free time.
71
+
72
+ <!-- end -->