Buckets:
| base_model: acrastt/IS-LM-3B | |
| datasets: | |
| - teknium/dataforge-economics | |
| language: | |
| - en | |
| library_name: transformers | |
| license: cc-by-sa-4.0 | |
| no_imatrix: iq1_s GGML_ASSERT(besti1 >= 0 && besti2 >= 0 && best_shift != 0) failed | |
| quantized_by: mradermacher | |
| ## About | |
| <!-- ### quantize_version: 2 --> | |
| <!-- ### output_tensor_quantised: 1 --> | |
| <!-- ### convert_type: hf --> | |
| <!-- ### vocab_type: --> | |
| <!-- ### tags: --> | |
| static quants of https://huggingface.co/acrastt/IS-LM-3B | |
| <!-- provided-files --> | |
| ## 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/IS-LM-3B-GGUF/resolve/main/IS-LM-3B.Q2_K.gguf) | Q2_K | 1.2 | | | |
| | [GGUF](https://huggingface.co/mradermacher/IS-LM-3B-GGUF/resolve/main/IS-LM-3B.Q3_K_S.gguf) | Q3_K_S | 1.4 | | | |
| | [GGUF](https://huggingface.co/mradermacher/IS-LM-3B-GGUF/resolve/main/IS-LM-3B.Q3_K_M.gguf) | Q3_K_M | 1.5 | lower quality | | |
| | [GGUF](https://huggingface.co/mradermacher/IS-LM-3B-GGUF/resolve/main/IS-LM-3B.Q3_K_L.gguf) | Q3_K_L | 1.6 | | | |
| | [GGUF](https://huggingface.co/mradermacher/IS-LM-3B-GGUF/resolve/main/IS-LM-3B.IQ4_XS.gguf) | IQ4_XS | 1.6 | | | |
| | [GGUF](https://huggingface.co/mradermacher/IS-LM-3B-GGUF/resolve/main/IS-LM-3B.Q4_K_S.gguf) | Q4_K_S | 1.7 | fast, recommended | | |
| | [GGUF](https://huggingface.co/mradermacher/IS-LM-3B-GGUF/resolve/main/IS-LM-3B.Q4_K_M.gguf) | Q4_K_M | 1.8 | fast, recommended | | |
| | [GGUF](https://huggingface.co/mradermacher/IS-LM-3B-GGUF/resolve/main/IS-LM-3B.Q5_K_S.gguf) | Q5_K_S | 2.0 | | | |
| | [GGUF](https://huggingface.co/mradermacher/IS-LM-3B-GGUF/resolve/main/IS-LM-3B.Q5_K_M.gguf) | Q5_K_M | 2.1 | | | |
| | [GGUF](https://huggingface.co/mradermacher/IS-LM-3B-GGUF/resolve/main/IS-LM-3B.Q6_K.gguf) | Q6_K | 2.4 | very good quality | | |
| | [GGUF](https://huggingface.co/mradermacher/IS-LM-3B-GGUF/resolve/main/IS-LM-3B.Q8_0.gguf) | Q8_0 | 3.1 | fast, best quality | | |
| | [GGUF](https://huggingface.co/mradermacher/IS-LM-3B-GGUF/resolve/main/IS-LM-3B.f16.gguf) | f16 | 5.7 | 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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