初始化项目,由ModelHub XC社区提供模型

Model: mradermacher/SmolVLM-256M-Instruct-GGUF
Source: Original Platform
This commit is contained in:
ModelHub XC
2026-08-26 17:30:16 +08:00
commit c21d66636e
14 changed files with 155 additions and 0 deletions

47
.gitattributes vendored Normal file
View File

@@ -0,0 +1,47 @@
*.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
SmolVLM-256M-Instruct.IQ4_XS.gguf filter=lfs diff=lfs merge=lfs -text
SmolVLM-256M-Instruct.Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
SmolVLM-256M-Instruct.Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
SmolVLM-256M-Instruct.Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
SmolVLM-256M-Instruct.Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
SmolVLM-256M-Instruct.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
SmolVLM-256M-Instruct.Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
SmolVLM-256M-Instruct.Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
SmolVLM-256M-Instruct.Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
SmolVLM-256M-Instruct.Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
SmolVLM-256M-Instruct.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
SmolVLM-256M-Instruct.f16.gguf filter=lfs diff=lfs merge=lfs -text

72
README.md Normal file
View File

@@ -0,0 +1,72 @@
---
base_model: HuggingFaceTB/SmolVLM-256M-Instruct
datasets:
- HuggingFaceM4/the_cauldron
- HuggingFaceM4/Docmatix
language:
- en
library_name: transformers
license: apache-2.0
mradermacher:
readme_rev: 1
quantized_by: mradermacher
---
## About
<!-- ### quantize_version: 2 -->
<!-- ### output_tensor_quantised: 1 -->
<!-- ### convert_type: hf -->
<!-- ### vocab_type: -->
<!-- ### tags: -->
static quants of https://huggingface.co/HuggingFaceTB/SmolVLM-256M-Instruct
<!-- provided-files -->
***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#SmolVLM-256M-Instruct-GGUF).***
weighted/imatrix quants are available at https://huggingface.co/mradermacher/SmolVLM-256M-Instruct-i1-GGUF
## 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/SmolVLM-256M-Instruct-GGUF/resolve/main/SmolVLM-256M-Instruct.Q2_K.gguf) | Q2_K | 0.2 | |
| [GGUF](https://huggingface.co/mradermacher/SmolVLM-256M-Instruct-GGUF/resolve/main/SmolVLM-256M-Instruct.Q3_K_S.gguf) | Q3_K_S | 0.2 | |
| [GGUF](https://huggingface.co/mradermacher/SmolVLM-256M-Instruct-GGUF/resolve/main/SmolVLM-256M-Instruct.IQ4_XS.gguf) | IQ4_XS | 0.2 | |
| [GGUF](https://huggingface.co/mradermacher/SmolVLM-256M-Instruct-GGUF/resolve/main/SmolVLM-256M-Instruct.Q3_K_M.gguf) | Q3_K_M | 0.2 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/SmolVLM-256M-Instruct-GGUF/resolve/main/SmolVLM-256M-Instruct.Q3_K_L.gguf) | Q3_K_L | 0.2 | |
| [GGUF](https://huggingface.co/mradermacher/SmolVLM-256M-Instruct-GGUF/resolve/main/SmolVLM-256M-Instruct.Q4_K_S.gguf) | Q4_K_S | 0.2 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/SmolVLM-256M-Instruct-GGUF/resolve/main/SmolVLM-256M-Instruct.Q4_K_M.gguf) | Q4_K_M | 0.2 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/SmolVLM-256M-Instruct-GGUF/resolve/main/SmolVLM-256M-Instruct.Q5_K_S.gguf) | Q5_K_S | 0.2 | |
| [GGUF](https://huggingface.co/mradermacher/SmolVLM-256M-Instruct-GGUF/resolve/main/SmolVLM-256M-Instruct.Q5_K_M.gguf) | Q5_K_M | 0.2 | |
| [GGUF](https://huggingface.co/mradermacher/SmolVLM-256M-Instruct-GGUF/resolve/main/SmolVLM-256M-Instruct.Q6_K.gguf) | Q6_K | 0.3 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/SmolVLM-256M-Instruct-GGUF/resolve/main/SmolVLM-256M-Instruct.Q8_0.gguf) | Q8_0 | 0.3 | fast, best quality |
| [GGUF](https://huggingface.co/mradermacher/SmolVLM-256M-Instruct-GGUF/resolve/main/SmolVLM-256M-Instruct.f16.gguf) | f16 | 0.4 | 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 -->

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:3b081b3dc37cd5b103025a1946d3ebd9e30619b8a4b8c2cadbb86a2a9f2489fd
size 107363456

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:128ed7547e8f7bbacfeb2be3ae7e7a9e890be84fd89d3951a2b3ff27a502aaff
size 104253056

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:258a7c34d259962263582720a652f5a180a03639ed795b67f5e597e4b136cf76
size 113584256

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:710c06f4eef146d1df39fd5fd2b94f1658645acb5780db679d6943eef63152e1
size 109561472

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:fb9d67e0206f5a7707565caa1ae702978764c7501deab4c61ff25068b93b6c28
size 104253056

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:04a8bb3fe980594e26f0227c9aa05298ac69cdc95b68d614352d520335c62e46
size 125053568

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:78f1e98161f605d3fe43b87c332b725691c5626d2d562a6a4351ff4339164b61
size 121639040

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:9fe1bdf16537062363de6e1246a8db4fc12667c8aa46e4664433c0627cfbb6c7
size 133476992

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:968d70b8e8f2bab77b24eb55a78e43c84befe09a2d18e9799f46b7c04d72bfe8
size 131348096

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:e9a7d93be767c768ea82adbf3ced506936a3350a055581d663e697b683331b37
size 168626816

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:ccf0368c60f7331aa9b8e27d35d7155a219252c088e264c93021e02b89f4fd61
size 175054976

View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:1d0bf397a2b56898df8607d036a9ad6e4eca7c292fe0dee530627bd282f435af
size 327810176