Buckets:
| base_model: fancyfeast/llama-joycaption-beta-one-hf-llava | |
| language: | |
| - en | |
| library_name: transformers | |
| mradermacher: | |
| readme_rev: 1 | |
| quantized_by: mradermacher | |
| tags: | |
| - captioning | |
| ## About | |
| <!-- ### quantize_version: 2 --> | |
| <!-- ### output_tensor_quantised: 1 --> | |
| <!-- ### convert_type: hf --> | |
| <!-- ### vocab_type: --> | |
| <!-- ### tags: --> | |
| static quants of https://huggingface.co/fancyfeast/llama-joycaption-beta-one-hf-llava | |
| <!-- provided-files --> | |
| ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#llama-joycaption-beta-one-hf-llava-GGUF).*** | |
| weighted/imatrix quants are available at https://huggingface.co/mradermacher/llama-joycaption-beta-one-hf-llava-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/llama-joycaption-beta-one-hf-llava-GGUF/resolve/main/llama-joycaption-beta-one-hf-llava.Q2_K.gguf) | Q2_K | 3.3 | | | |
| | [GGUF](https://huggingface.co/mradermacher/llama-joycaption-beta-one-hf-llava-GGUF/resolve/main/llama-joycaption-beta-one-hf-llava.Q3_K_S.gguf) | Q3_K_S | 3.8 | | | |
| | [GGUF](https://huggingface.co/mradermacher/llama-joycaption-beta-one-hf-llava-GGUF/resolve/main/llama-joycaption-beta-one-hf-llava.Q3_K_M.gguf) | Q3_K_M | 4.1 | lower quality | | |
| | [GGUF](https://huggingface.co/mradermacher/llama-joycaption-beta-one-hf-llava-GGUF/resolve/main/llama-joycaption-beta-one-hf-llava.Q3_K_L.gguf) | Q3_K_L | 4.4 | | | |
| | [GGUF](https://huggingface.co/mradermacher/llama-joycaption-beta-one-hf-llava-GGUF/resolve/main/llama-joycaption-beta-one-hf-llava.IQ4_XS.gguf) | IQ4_XS | 4.6 | | | |
| | [GGUF](https://huggingface.co/mradermacher/llama-joycaption-beta-one-hf-llava-GGUF/resolve/main/llama-joycaption-beta-one-hf-llava.Q4_K_S.gguf) | Q4_K_S | 4.8 | fast, recommended | | |
| | [GGUF](https://huggingface.co/mradermacher/llama-joycaption-beta-one-hf-llava-GGUF/resolve/main/llama-joycaption-beta-one-hf-llava.Q4_K_M.gguf) | Q4_K_M | 5.0 | fast, recommended | | |
| | [GGUF](https://huggingface.co/mradermacher/llama-joycaption-beta-one-hf-llava-GGUF/resolve/main/llama-joycaption-beta-one-hf-llava.Q5_K_S.gguf) | Q5_K_S | 5.7 | | | |
| | [GGUF](https://huggingface.co/mradermacher/llama-joycaption-beta-one-hf-llava-GGUF/resolve/main/llama-joycaption-beta-one-hf-llava.Q5_K_M.gguf) | Q5_K_M | 5.8 | | | |
| | [GGUF](https://huggingface.co/mradermacher/llama-joycaption-beta-one-hf-llava-GGUF/resolve/main/llama-joycaption-beta-one-hf-llava.Q6_K.gguf) | Q6_K | 6.7 | very good quality | | |
| | [GGUF](https://huggingface.co/mradermacher/llama-joycaption-beta-one-hf-llava-GGUF/resolve/main/llama-joycaption-beta-one-hf-llava.Q8_0.gguf) | Q8_0 | 8.6 | fast, best quality | | |
| | [GGUF](https://huggingface.co/mradermacher/llama-joycaption-beta-one-hf-llava-GGUF/resolve/main/llama-joycaption-beta-one-hf-llava.f16.gguf) | f16 | 16.2 | 16 bpw, overkill | | |
| Here is a handy graph by ikawrakow comparing some lower-quality quant | |
| types (lower is better): | |
|  | |
| 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 --> | |
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