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@@ -1,79 +1,91 @@
1
- ---
2
- base_model: Qwen/Qwen2.5-1.5B-Instruct
3
- language:
4
- - en
5
- library_name: transformers
6
- license: apache-2.0
7
- license_link: https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct/blob/main/LICENSE
8
- quantized_by: mradermacher
9
- tags:
10
- - chat
11
- ---
12
- ## About
13
-
14
- <!-- ### quantize_version: 2 -->
15
- <!-- ### output_tensor_quantised: 1 -->
16
- <!-- ### convert_type: hf -->
17
- <!-- ### vocab_type: -->
18
- <!-- ### tags: -->
19
- static quants of https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct
20
-
21
- <!-- provided-files -->
22
- weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-i1-GGUF
23
- ## Usage
24
-
25
- If you are unsure how to use GGUF files, refer to one of [TheBloke's
26
- READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
27
- more details, including on how to concatenate multi-part files.
28
-
29
- ## Provided Quants
30
-
31
- (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
32
-
33
- | Link | Type | Size/GB | Notes |
34
- |:-----|:-----|--------:|:------|
35
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q2_K.gguf) | Q2_K | 0.8 | |
36
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.IQ3_XS.gguf) | IQ3_XS | 0.8 | |
37
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q3_K_S.gguf) | Q3_K_S | 0.9 | |
38
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.IQ3_S.gguf) | IQ3_S | 0.9 | beats Q3_K* |
39
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.IQ3_M.gguf) | IQ3_M | 0.9 | |
40
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q3_K_M.gguf) | Q3_K_M | 0.9 | lower quality |
41
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q3_K_L.gguf) | Q3_K_L | 1.0 | |
42
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.IQ4_XS.gguf) | IQ4_XS | 1.0 | |
43
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q4_0.gguf) | Q4_0 | 1.0 | fast, low quality |
44
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q4_0_4_4.gguf) | Q4_0_4_4 | 1.0 | fast on arm, low quality |
45
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q4_0_4_8.gguf) | Q4_0_4_8 | 1.0 | fast on arm+i8mm, low quality |
46
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q4_0_8_8.gguf) | Q4_0_8_8 | 1.0 | fast on arm+sve, low quality |
47
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q4_K_S.gguf) | Q4_K_S | 1.0 | fast, recommended |
48
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.IQ4_NL.gguf) | IQ4_NL | 1.0 | prefer IQ4_XS |
49
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q4_K_M.gguf) | Q4_K_M | 1.1 | fast, recommended |
50
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q4_1.gguf) | Q4_1 | 1.1 | |
51
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q5_0.gguf) | Q5_0 | 1.2 | |
52
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q5_K_S.gguf) | Q5_K_S | 1.2 | |
53
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q5_K_M.gguf) | Q5_K_M | 1.2 | |
54
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q5_1.gguf) | Q5_1 | 1.3 | |
55
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q6_K.gguf) | Q6_K | 1.4 | very good quality |
56
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q8_0.gguf) | Q8_0 | 1.7 | fast, best quality |
57
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.SOURCE.gguf) | SOURCE | 3.2 | source gguf, only provided when it was hard to come by |
58
- | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.f16.gguf) | f16 | 3.2 | 16 bpw, overkill |
59
-
60
- Here is a handy graph by ikawrakow comparing some lower-quality quant
61
- types (lower is better):
62
-
63
- ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
64
-
65
- And here are Artefact2's thoughts on the matter:
66
- https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
67
-
68
- ## FAQ / Model Request
69
-
70
- See https://huggingface.co/mradermacher/model_requests for some answers to
71
- questions you might have and/or if you want some other model quantized.
72
-
73
- ## Thanks
74
-
75
- I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
76
- me use its servers and providing upgrades to my workstation to enable
77
- 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.
78
-
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- <!-- end -->
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: Qwen/Qwen2.5-1.5B-Instruct
3
+ language:
4
+ - zho
5
+ - eng
6
+ - fra
7
+ - spa
8
+ - por
9
+ - deu
10
+ - ita
11
+ - rus
12
+ - jpn
13
+ - kor
14
+ - vie
15
+ - tha
16
+ - ara
17
+ library_name: transformers
18
+ license: apache-2.0
19
+ license_link: https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct/blob/main/LICENSE
20
+ quantized_by: mradermacher
21
+ tags:
22
+ - chat
23
+ ---
24
+ ## About
25
+
26
+ <!-- ### quantize_version: 2 -->
27
+ <!-- ### output_tensor_quantised: 1 -->
28
+ <!-- ### convert_type: hf -->
29
+ <!-- ### vocab_type: -->
30
+ <!-- ### tags: -->
31
+ static quants of https://huggingface.co/Qwen/Qwen2.5-1.5B-Instruct
32
+
33
+ <!-- provided-files -->
34
+ weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-i1-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/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q2_K.gguf) | Q2_K | 0.8 | |
48
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.IQ3_XS.gguf) | IQ3_XS | 0.8 | |
49
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q3_K_S.gguf) | Q3_K_S | 0.9 | |
50
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.IQ3_S.gguf) | IQ3_S | 0.9 | beats Q3_K* |
51
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.IQ3_M.gguf) | IQ3_M | 0.9 | |
52
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q3_K_M.gguf) | Q3_K_M | 0.9 | lower quality |
53
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q3_K_L.gguf) | Q3_K_L | 1.0 | |
54
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.IQ4_XS.gguf) | IQ4_XS | 1.0 | |
55
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q4_0.gguf) | Q4_0 | 1.0 | fast, low quality |
56
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q4_0_4_4.gguf) | Q4_0_4_4 | 1.0 | fast on arm, low quality |
57
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q4_0_4_8.gguf) | Q4_0_4_8 | 1.0 | fast on arm+i8mm, low quality |
58
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q4_0_8_8.gguf) | Q4_0_8_8 | 1.0 | fast on arm+sve, low quality |
59
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q4_K_S.gguf) | Q4_K_S | 1.0 | fast, recommended |
60
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.IQ4_NL.gguf) | IQ4_NL | 1.0 | prefer IQ4_XS |
61
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q4_K_M.gguf) | Q4_K_M | 1.1 | fast, recommended |
62
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q4_1.gguf) | Q4_1 | 1.1 | |
63
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q5_0.gguf) | Q5_0 | 1.2 | |
64
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q5_K_S.gguf) | Q5_K_S | 1.2 | |
65
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q5_K_M.gguf) | Q5_K_M | 1.2 | |
66
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q5_1.gguf) | Q5_1 | 1.3 | |
67
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q6_K.gguf) | Q6_K | 1.4 | very good quality |
68
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.Q8_0.gguf) | Q8_0 | 1.7 | fast, best quality |
69
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.SOURCE.gguf) | SOURCE | 3.2 | source gguf, only provided when it was hard to come by |
70
+ | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-1.5B-Instruct-GGUF/resolve/main/Qwen2.5-1.5B-Instruct.f16.gguf) | f16 | 3.2 | 16 bpw, overkill |
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 -->