Transformers
GGUF
English
Inference Endpoints
mradermacher commited on
Commit
d99a100
1 Parent(s): 5e4eb14

auto-patch README.md

Browse files
Files changed (1) hide show
  1. README.md +58 -0
README.md CHANGED
@@ -1,5 +1,63 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  <!-- ### quantize_version: 1 -->
2
  <!-- ### output_tensor_quantised: 1 -->
3
  <!-- ### convert_type: -->
4
  <!-- ### vocab_type: -->
5
  static quants of https://huggingface.co/totally-not-an-llm/PuddleJumper-13b
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ datasets:
3
+ - totally-not-an-llm/EverythingLM-data-V2
4
+ - garage-bAInd/Open-Platypus
5
+ - Open-Orca/OpenOrca
6
+ exported_from: totally-not-an-llm/PuddleJumper-13b
7
+ language:
8
+ - en
9
+ library_name: transformers
10
+ license: llama2
11
+ quantized_by: mradermacher
12
+ ---
13
+ ## About
14
+
15
  <!-- ### quantize_version: 1 -->
16
  <!-- ### output_tensor_quantised: 1 -->
17
  <!-- ### convert_type: -->
18
  <!-- ### vocab_type: -->
19
  static quants of https://huggingface.co/totally-not-an-llm/PuddleJumper-13b
20
+
21
+
22
+ <!-- provided-files -->
23
+ 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.
24
+ ## Usage
25
+
26
+ If you are unsure how to use GGUF files, refer to one of [TheBloke's
27
+ READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
28
+ more details, including on how to concatenate multi-part files.
29
+
30
+ ## Provided Quants
31
+
32
+ (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
33
+
34
+ | Link | Type | Size/GB | Notes |
35
+ |:-----|:-----|--------:|:------|
36
+ | [GGUF](https://huggingface.co/mradermacher/PuddleJumper-13b-GGUF/resolve/main/PuddleJumper-13b.Q2_K.gguf) | Q2_K | 5.0 | |
37
+ | [GGUF](https://huggingface.co/mradermacher/PuddleJumper-13b-GGUF/resolve/main/PuddleJumper-13b.IQ3_S.gguf) | IQ3_S | 5.8 | beats Q3_K* |
38
+ | [GGUF](https://huggingface.co/mradermacher/PuddleJumper-13b-GGUF/resolve/main/PuddleJumper-13b.Q3_K_S.gguf) | Q3_K_S | 5.8 | |
39
+ | [GGUF](https://huggingface.co/mradermacher/PuddleJumper-13b-GGUF/resolve/main/PuddleJumper-13b.IQ3_M.gguf) | IQ3_M | 6.1 | |
40
+ | [GGUF](https://huggingface.co/mradermacher/PuddleJumper-13b-GGUF/resolve/main/PuddleJumper-13b.Q3_K_M.gguf) | Q3_K_M | 6.4 | lower quality |
41
+ | [GGUF](https://huggingface.co/mradermacher/PuddleJumper-13b-GGUF/resolve/main/PuddleJumper-13b.Q3_K_L.gguf) | Q3_K_L | 7.0 | |
42
+ | [GGUF](https://huggingface.co/mradermacher/PuddleJumper-13b-GGUF/resolve/main/PuddleJumper-13b.Q4_K_S.gguf) | Q4_K_S | 7.5 | fast, recommended |
43
+ | [GGUF](https://huggingface.co/mradermacher/PuddleJumper-13b-GGUF/resolve/main/PuddleJumper-13b.Q4_K_M.gguf) | Q4_K_M | 8.0 | fast, recommended |
44
+ | [GGUF](https://huggingface.co/mradermacher/PuddleJumper-13b-GGUF/resolve/main/PuddleJumper-13b.Q5_K_S.gguf) | Q5_K_S | 9.1 | |
45
+ | [GGUF](https://huggingface.co/mradermacher/PuddleJumper-13b-GGUF/resolve/main/PuddleJumper-13b.Q6_K.gguf) | Q6_K | 10.8 | very good quality |
46
+ | [GGUF](https://huggingface.co/mradermacher/PuddleJumper-13b-GGUF/resolve/main/PuddleJumper-13b.Q8_0.gguf) | Q8_0 | 13.9 | fast, best quality |
47
+
48
+
49
+ Here is a handy graph by ikawrakow comparing some lower-quality quant
50
+ types (lower is better):
51
+
52
+ ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
53
+
54
+ And here are Artefact2's thoughts on the matter:
55
+ https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
56
+
57
+ ## Thanks
58
+
59
+ I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
60
+ me use its servers and providing upgrades to my workstation to enable
61
+ this work in my free time.
62
+
63
+ <!-- end -->