mradermacher commited on
Commit
d26fdae
1 Parent(s): fb29cf6

auto-patch README.md

Browse files
Files changed (1) hide show
  1. README.md +50 -0
README.md CHANGED
@@ -1,6 +1,56 @@
 
 
 
 
 
 
 
 
 
 
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/leafspark/Reflection-Llama-3.1-70B-bf16
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: leafspark/Reflection-Llama-3.1-70B-bf16
3
+ language:
4
+ - en
5
+ library_name: transformers
6
+ license: llama3.1
7
+ quantized_by: mradermacher
8
+ ---
9
+ ## About
10
+
11
  <!-- ### quantize_version: 2 -->
12
  <!-- ### output_tensor_quantised: 1 -->
13
  <!-- ### convert_type: hf -->
14
  <!-- ### vocab_type: -->
15
  <!-- ### tags: -->
16
  static quants of https://huggingface.co/leafspark/Reflection-Llama-3.1-70B-bf16
17
+
18
+ <!-- provided-files -->
19
+ 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.
20
+ ## Usage
21
+
22
+ If you are unsure how to use GGUF files, refer to one of [TheBloke's
23
+ READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
24
+ more details, including on how to concatenate multi-part files.
25
+
26
+ ## Provided Quants
27
+
28
+ (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
29
+
30
+ | Link | Type | Size/GB | Notes |
31
+ |:-----|:-----|--------:|:------|
32
+ | [GGUF](https://huggingface.co/mradermacher/Reflection-Llama-3.1-70B-bf16-GGUF/resolve/main/Reflection-Llama-3.1-70B-bf16.Q2_K.gguf) | Q2_K | 26.5 | |
33
+ | [GGUF](https://huggingface.co/mradermacher/Reflection-Llama-3.1-70B-bf16-GGUF/resolve/main/Reflection-Llama-3.1-70B-bf16.IQ3_S.gguf) | IQ3_S | 31.0 | beats Q3_K* |
34
+ | [GGUF](https://huggingface.co/mradermacher/Reflection-Llama-3.1-70B-bf16-GGUF/resolve/main/Reflection-Llama-3.1-70B-bf16.Q4_K_S.gguf) | Q4_K_S | 40.4 | fast, recommended |
35
+ | [PART 1](https://huggingface.co/mradermacher/Reflection-Llama-3.1-70B-bf16-GGUF/resolve/main/Reflection-Llama-3.1-70B-bf16.Q8_0.gguf.part1of2) [PART 2](https://huggingface.co/mradermacher/Reflection-Llama-3.1-70B-bf16-GGUF/resolve/main/Reflection-Llama-3.1-70B-bf16.Q8_0.gguf.part2of2) | Q8_0 | 75.1 | fast, best quality |
36
+
37
+ Here is a handy graph by ikawrakow comparing some lower-quality quant
38
+ types (lower is better):
39
+
40
+ ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
41
+
42
+ And here are Artefact2's thoughts on the matter:
43
+ https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
44
+
45
+ ## FAQ / Model Request
46
+
47
+ See https://huggingface.co/mradermacher/model_requests for some answers to
48
+ questions you might have and/or if you want some other model quantized.
49
+
50
+ ## Thanks
51
+
52
+ I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
53
+ me use its servers and providing upgrades to my workstation to enable
54
+ this work in my free time.
55
+
56
+ <!-- end -->