mradermacher/ChemWiz_16bit-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/ChemWiz_16bit-GGUF
Source: Original Platform
This commit is contained in:
ModelHub XC
2026-06-10 23:38:21 +08:00
commit 6e69be9ebe
14 changed files with 152 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

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
ChemWiz_16bit.f16.gguf filter=lfs diff=lfs merge=lfs -text
ChemWiz_16bit.Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
ChemWiz_16bit.Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
ChemWiz_16bit.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
ChemWiz_16bit.Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
ChemWiz_16bit.Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
ChemWiz_16bit.Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
ChemWiz_16bit.Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
ChemWiz_16bit.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
ChemWiz_16bit.Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
ChemWiz_16bit.Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
ChemWiz_16bit.IQ4_XS.gguf filter=lfs diff=lfs merge=lfs -text

3
ChemWiz_16bit.IQ4_XS.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:9fa5cd4f120817e7906c3a12ed0e38ba2c216001f67439870c31988315e8edd6
size 4250297536

3
ChemWiz_16bit.Q2_K.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:5f5f991e6ac4d0644adedec24fa1b27c45ebbbad5a798c518147b7f5db7ba7c3
size 3015939264

3
ChemWiz_16bit.Q3_K_L.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:a63265a1a9d2dd10070c8194ef151382169b5afde9e8d52b97dc19dc63ead8f0
size 4088458432

3
ChemWiz_16bit.Q3_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:9b7b01e71b97ef2200cb78aba0ad6152591cabf9ee93c9f5015d6ad8e8f90dea
size 3808390336

3
ChemWiz_16bit.Q3_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:a7a441b38f0cf8ce848b7298a19d3871facf41ab41f3ad02c2adfd91ff50c338
size 3492367552

3
ChemWiz_16bit.Q4_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:cc664c5e57936ce828234d7fb775a9f248dc36e90782a991384dba9f073f3a57
size 4683072704

3
ChemWiz_16bit.Q4_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:fe22ca55da7f630fbbb7eabbfd5004ac662c62fc64287a2a38f0fb506092e49e
size 4457768128

3
ChemWiz_16bit.Q5_K_M.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:274e32185e0e45d957d6b91dd51aa1a4c6aa9fc0bf1679bcaad15b3166fe20ca
size 5444830400

3
ChemWiz_16bit.Q5_K_S.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:0b653600ee458864581bfbc84b3cee2acb6b1ebefa0819b5072f4d7a35bd8695
size 5315175616

3
ChemWiz_16bit.Q6_K.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:dee2e4e1c5b392a3d3319b1567fc497a7db1560f2c68206c04494cb187a3a69f
size 6254197952

3
ChemWiz_16bit.Q8_0.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:c3087838caf516ae4460b0aa3110e1acb544ae9f743bb281db8c021d8cc2a907
size 8098524352

3
ChemWiz_16bit.f16.gguf Normal file
View File

@@ -0,0 +1,3 @@
version https://git-lfs.github.com/spec/v1
oid sha256:5f6ee30ee3ada0ecea840a5c9335d0c71564f38017bf10da6f6e53526c99a7c9
size 15237852352

69
README.md Normal file
View File

@@ -0,0 +1,69 @@
---
base_model: dbands/ChemWiz_16bit
datasets:
- Vezora/Open-Critic-GPT
- dbands/ChemistryCoder
- iamtarun/python_code_instructions_18k_alpaca
- AI-MO/NuminaMath-CoT
- AdaptLLM/med_knowledge_prob
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/dbands/ChemWiz_16bit
<!-- provided-files -->
weighted/imatrix quants are available at https://huggingface.co/mradermacher/ChemWiz_16bit-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/ChemWiz_16bit-GGUF/resolve/main/ChemWiz_16bit.Q2_K.gguf) | Q2_K | 3.1 | |
| [GGUF](https://huggingface.co/mradermacher/ChemWiz_16bit-GGUF/resolve/main/ChemWiz_16bit.Q3_K_S.gguf) | Q3_K_S | 3.6 | |
| [GGUF](https://huggingface.co/mradermacher/ChemWiz_16bit-GGUF/resolve/main/ChemWiz_16bit.Q3_K_M.gguf) | Q3_K_M | 3.9 | lower quality |
| [GGUF](https://huggingface.co/mradermacher/ChemWiz_16bit-GGUF/resolve/main/ChemWiz_16bit.Q3_K_L.gguf) | Q3_K_L | 4.2 | |
| [GGUF](https://huggingface.co/mradermacher/ChemWiz_16bit-GGUF/resolve/main/ChemWiz_16bit.IQ4_XS.gguf) | IQ4_XS | 4.4 | |
| [GGUF](https://huggingface.co/mradermacher/ChemWiz_16bit-GGUF/resolve/main/ChemWiz_16bit.Q4_K_S.gguf) | Q4_K_S | 4.6 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/ChemWiz_16bit-GGUF/resolve/main/ChemWiz_16bit.Q4_K_M.gguf) | Q4_K_M | 4.8 | fast, recommended |
| [GGUF](https://huggingface.co/mradermacher/ChemWiz_16bit-GGUF/resolve/main/ChemWiz_16bit.Q5_K_S.gguf) | Q5_K_S | 5.4 | |
| [GGUF](https://huggingface.co/mradermacher/ChemWiz_16bit-GGUF/resolve/main/ChemWiz_16bit.Q5_K_M.gguf) | Q5_K_M | 5.5 | |
| [GGUF](https://huggingface.co/mradermacher/ChemWiz_16bit-GGUF/resolve/main/ChemWiz_16bit.Q6_K.gguf) | Q6_K | 6.4 | very good quality |
| [GGUF](https://huggingface.co/mradermacher/ChemWiz_16bit-GGUF/resolve/main/ChemWiz_16bit.Q8_0.gguf) | Q8_0 | 8.2 | fast, best quality |
| [GGUF](https://huggingface.co/mradermacher/ChemWiz_16bit-GGUF/resolve/main/ChemWiz_16bit.f16.gguf) | f16 | 15.3 | 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 -->