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For a convenient overview and download list, visit our model page for this model.
Fonte do modelo
Descrição da fonte
static quants of https://huggingface.co/opendatalab/TRivia-3B
For a convenient overview and download list, visit our model page for this model.
weighted/imatrix quants are available at
Fontes
1 fonteVerificado 17 de set.
Artefatos de modelo
14 artefatosTrechos de fonte
2 trechosIf you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.
(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
| Link | Type | Size/GB | Notes |
|---|---|---|---|
| GGUF | mmproj-Q8_0 | 0.9 | multi-modal supplement |
| GGUF | mmproj-f16 | 1.4 | multi-modal supplement |
| GGUF | Q2_K | 1.5 | |
| GGUF | Q3_K_S | 1.7 | |
| GGUF |
Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):
image.png
And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.
I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.
TRivia-3B.mmproj-f16.gguf
gguf · 1,25 GB · SHA-256 a760961f57b1…4827 · Hugging Face
--- base_model: opendatalab/TRivia-3B language: - en - zh - multilingual library_name: transformers mradermacher: readme_rev: 1 quantized_by: mradermacher tags: - table recognition - image-to-text - table --- ## About <!-- ### quantize_version: 2 --> <!-- ### output_tensor_quantised: 1 --> <!-- ### convert_type: hf --> <!-- ### vocab_type: --> <!-- ### tags: --> <!-- ### quants: x-f16 Q4_K_S Q2_K Q8_0 Q6_K Q3_K_M Q3_K_S Q3_K_L Q4_K_M Q5_K_S Q5_K_M IQ4_XS --> <!-- ### quants_skip: --> <!-- ### skip_mmproj: --> static quants of https://huggingface.co/opendatalab/TRivia-3B <!-- provided-files --> ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#TRivia-3B-GGUF).*** weighted/imatrix quants are available at https://huggingface.co/mradermacher/TRivia-3B-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/TRivia-3B-GGUF/resolve/main/TRivia-3B.mmproj-Q8_0.gguf) | mmproj-Q8_0 | 0.9 | multi-modal supplement | | [GGUF](https://huggingface.co/mradermacher/TRivia-3B-GGUF/resolve/main/TRivia-3B.mmproj-f16.gguf) | mmproj-f16 | 1.4 | multi-modal supplement | | [GGUF](https://huggingface.co/mradermacher/TRivia-3B-GGUF/resolve/main/TRivia-3B.Q2_K.gguf) | Q2_K | 1.5 | | | [GGUF](https://huggingface.co/mradermacher/TRivia-3B-GGUF/resolve/main/TRivia-3B.Q3_K_S.gguf) | Q3_K_S | 1.7 | | | [GGUF](https://huggingface.co/mradermacher/TRivia-3B-GGUF/resolve/main/TRivia-3B.Q3_K_M.gguf) | Q3_K_M | 1.8 | lower quality | | [GGUF](https://huggingface.co/mradermacher/TRivia-3B-GGUF/resolve/main/TRivia-3B.Q3_K_L.gguf) | Q3_K_L | 1.9 | | | [GGUF](https://huggingface.co/mradermacher/TRivia-3B-GGUF/resolve/main/TRivia-3B.IQ4_XS.gguf) | IQ4_XS | 2.0 | | | [GGUF](https://huggingface.co/mradermacher/TRivia-3B-GGUF/resolve/main/TRivia-3B.Q4_K_S.gguf) | Q4_K_S | 2.1 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/TRivia-3B-GGUF/resolve/main/TRivia-3B.Q4_K_M.gguf) | Q4_K_M | 2.2 | fast, recommended | | [GGU...
Source context: 408 downloads · 0 likes · Pipeline image-to-text · Library transformers · Repo mradermacher/TRivia-3B-GGUF
| Q3_K_M |
| 1.8 |
| lower quality |
| GGUF | Q3_K_L | 1.9 |
| GGUF | IQ4_XS | 2.0 |
| GGUF | Q4_K_S | 2.1 | fast, recommended |
| GGUF | Q4_K_M | 2.2 | fast, recommended |
| GGUF | Q5_K_S | 2.5 |
| GGUF | Q5_K_M | 2.5 |
| GGUF | Q6_K | 2.9 | very good quality |
| GGUF | Q8_0 | 3.7 | fast, best quality |
| GGUF | f16 | 6.9 | 16 bpw, overkill |
