mradermacher/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained-GGUF
1
0
Fork 0
Code Issues Pull Requests Actions Projects Releases Wiki Activity

初始化项目，由ModelHub XC社区提供模型

Browse Source 
Model: mradermacher/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained-GGUF
Source: Original Platform
This commit is contained in:
ModelHub XC
2026-08-04 18:01:16 +08:00
commit 044bd0a508
15 changed files with 153 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

48
.gitattributes vendored Normal file
View File

@@ -0,0 +1,48 @@
*.7z filter=lfs diff=lfs merge=lfs -text
*.arrow filter=lfs diff=lfs merge=lfs -text
*.bin filter=lfs diff=lfs merge=lfs -text
*.bz2 filter=lfs diff=lfs merge=lfs -text
*.ckpt filter=lfs diff=lfs merge=lfs -text
*.ftz filter=lfs diff=lfs merge=lfs -text
*.gz filter=lfs diff=lfs merge=lfs -text
*.h5 filter=lfs diff=lfs merge=lfs -text
*.joblib filter=lfs diff=lfs merge=lfs -text
*.lfs.* filter=lfs diff=lfs merge=lfs -text
*.mlmodel filter=lfs diff=lfs merge=lfs -text
*.model filter=lfs diff=lfs merge=lfs -text
*.msgpack filter=lfs diff=lfs merge=lfs -text
*.npy filter=lfs diff=lfs merge=lfs -text
*.npz filter=lfs diff=lfs merge=lfs -text
*.onnx filter=lfs diff=lfs merge=lfs -text
*.ot filter=lfs diff=lfs merge=lfs -text
*.parquet filter=lfs diff=lfs merge=lfs -text
*.pb filter=lfs diff=lfs merge=lfs -text
*.pickle filter=lfs diff=lfs merge=lfs -text
*.pkl filter=lfs diff=lfs merge=lfs -text
*.pt filter=lfs diff=lfs merge=lfs -text
*.pth filter=lfs diff=lfs merge=lfs -text
*.rar filter=lfs diff=lfs merge=lfs -text
*.safetensors filter=lfs diff=lfs merge=lfs -text
saved_model/**/* filter=lfs diff=lfs merge=lfs -text
*.tar.* filter=lfs diff=lfs merge=lfs -text
*.tar filter=lfs diff=lfs merge=lfs -text
*.tflite filter=lfs diff=lfs merge=lfs -text
*.tgz filter=lfs diff=lfs merge=lfs -text
*.wasm filter=lfs diff=lfs merge=lfs -text
*.xz filter=lfs diff=lfs merge=lfs -text
*.zip filter=lfs diff=lfs merge=lfs -text
*.zst filter=lfs diff=lfs merge=lfs -text
*tfevents* filter=lfs diff=lfs merge=lfs -text
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.f16.gguf filter=lfs diff=lfs merge=lfs -text
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.IQ4_XS.gguf filter=lfs diff=lfs merge=lfs -text
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q4_0_4_4.gguf filter=lfs diff=lfs merge=lfs -text

3
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.IQ4_XS.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:7b72ddd75751b361a000ca83d4fb0a5d8aece6b53a8fdea97fb6ea8a50848bd4
size 3373775072

3
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q2_K.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:e74c904ff65373b30923fa80e3f226bbc4976e61225e5a6db699b89f715c7c2e
size 2508507360

3
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q3_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:ea507d0190fe1b0f03c87f7f19c2576b36273c5bfaebad46cee6ec5b387a2907
size 3280732384

3
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q3_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:ee597d8ea00911d67fbcf5f670034a06e580f394f1f5957db59b8ca72b0d38f1
size 3140550880

3
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q3_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:f4ed1950735d4be529b6a7e5dc9936019670ea8a77fad515fa32a0767488d3ed
size 2897936608

3
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q4_0_4_4.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:2945f1a77ea683d786f1d3dd40799ac3dbaa178655d1d14e3755a0388dbb52f9
size 3470694624

3
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q4_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:4a6aee7704af34e46ea2056720d1bd9eb24e84b20ec4d17d08a3cb02e3a1373f
size 3951892704

3
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q4_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:351e50b8014a99e36ce10feaea0349e9471c22b33779ae585f825eff6247c08e
size 3660945632

3
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q5_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:cd1ee6c6895ad788c95de32860e7d69d42c3edf3343ad18fdeab8dd417ba4350
size 4510619872

3
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q5_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:2a737ca9f47d90c71cfc054585b6ed760d92fb613c7aca516395cb8d6b5d056e
size 4269283552

3
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q6_K.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:b984bb81864a70940218d04d8f29bbb5a80f94a0a7b86be3b2b0baae5a408e3f
size 5274579168

3
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q8_0.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:24eecf3bc282e13ce16529a11abee84cde0acfc15dc10b4d9385908b47e59896
size 6394380512

3
Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.f16.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:04121709d9d121e0577f8783d36cfcec9752ee9de105860bdcd1835abc38fe39
size 12026708192

66
README.md Normal file
View File

@@ -0,0 +1,66 @@
---
base_model: Na0s/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained
datasets:
- Na0s/sft-ready-Text-Generation-Augmented-Data-Alpaca-Format
language:
- en
library_name: transformers
quantized_by: mradermacher
---
## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
static quants of https://huggingface.co/Na0s/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained
<!-- provided-files -->
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.
## Usage
If you are unsure how to use GGUF files, refer to one of [TheBloke's
READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
more details, including on how to concatenate multi-part files.
## Provided Quants
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
| Link | Type | Size/GB | Notes |
|:-----|:-----|--------:|:------|
| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained-GGUF/resolve/main/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q2_K.gguf) | Q2_K | 2.6 | |
| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained-GGUF/resolve/main/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q3_K_S.gguf) | Q3_K_S | 3.0 | |
| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained-GGUF/resolve/main/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q3_K_M.gguf) | Q3_K_M | 3.2 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained-GGUF/resolve/main/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q3_K_L.gguf) | Q3_K_L | 3.4 | |
| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained-GGUF/resolve/main/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.IQ4_XS.gguf) | IQ4_XS | 3.5 | |
| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained-GGUF/resolve/main/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q4_0_4_4.gguf) | Q4_0_4_4 | 3.6 | fast on arm, low quality |
| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained-GGUF/resolve/main/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q4_K_S.gguf) | Q4_K_S | 3.8 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained-GGUF/resolve/main/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q4_K_M.gguf) | Q4_K_M | 4.1 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained-GGUF/resolve/main/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q5_K_S.gguf) | Q5_K_S | 4.4 | |
| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained-GGUF/resolve/main/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q5_K_M.gguf) | Q5_K_M | 4.6 | |
| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained-GGUF/resolve/main/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q6_K.gguf) | Q6_K | 5.4 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained-GGUF/resolve/main/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.Q8_0.gguf) | Q8_0 | 6.5 | fast, best quality |
| [GGUF](https://huggingface.co/mradermacher/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained-GGUF/resolve/main/Qwen1.5-MoE-A2.7B-20-experts-SFT-trained.f16.gguf) | f16 | 12.1 | 16 bpw, overkill |
Here is a handy graph by ikawrakow comparing some lower-quality quant
types (lower is better):
![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
And here are Artefact2's thoughts on the matter:
https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
## FAQ / Model Request
See https://huggingface.co/mradermacher/model_requests for some answers to
questions you might have and/or if you want some other model quantized.
## Thanks
I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
me use its servers and providing upgrades to my workstation to enable
this work in my free time.
<!-- end -->