--- base_model: huihui-ai/Qwen2.5-Coder-14B-Instruct-abliterated language: - en library_name: transformers license: apache-2.0 license_link: https://huggingface.co/huihui-ai/Qwen2.5-Coder-14B-Instruct-abliterate/blob/main/LICENSE no_imatrix: nan detected in blk.47.attn_q.weight quantized_by: mradermacher tags: - code - codeqwen - chat - qwen - qwen-coder - abliterated - uncensored --- ## About static quants of https://huggingface.co/huihui-ai/Qwen2.5-Coder-14B-Instruct-abliterated ## 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/Qwen2.5-Coder-14B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-Coder-14B-Instruct-abliterated.Q2_K.gguf) | Q2_K | 5.9 | | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Coder-14B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-Coder-14B-Instruct-abliterated.Q3_K_S.gguf) | Q3_K_S | 6.8 | | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Coder-14B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-Coder-14B-Instruct-abliterated.Q3_K_M.gguf) | Q3_K_M | 7.4 | lower quality | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Coder-14B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-Coder-14B-Instruct-abliterated.Q3_K_L.gguf) | Q3_K_L | 8.0 | | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Coder-14B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-Coder-14B-Instruct-abliterated.IQ4_XS.gguf) | IQ4_XS | 8.3 | | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Coder-14B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-Coder-14B-Instruct-abliterated.Q4_0_4_4.gguf) | Q4_0_4_4 | 8.6 | fast on arm, low quality | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Coder-14B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-Coder-14B-Instruct-abliterated.Q4_K_S.gguf) | Q4_K_S | 8.7 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Coder-14B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-Coder-14B-Instruct-abliterated.Q4_K_M.gguf) | Q4_K_M | 9.1 | fast, recommended | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Coder-14B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-Coder-14B-Instruct-abliterated.Q5_K_S.gguf) | Q5_K_S | 10.4 | | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Coder-14B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-Coder-14B-Instruct-abliterated.Q5_K_M.gguf) | Q5_K_M | 10.6 | | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Coder-14B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-Coder-14B-Instruct-abliterated.Q6_K.gguf) | Q6_K | 12.2 | very good quality | | [GGUF](https://huggingface.co/mradermacher/Qwen2.5-Coder-14B-Instruct-abliterated-GGUF/resolve/main/Qwen2.5-Coder-14B-Instruct-abliterated.Q8_0.gguf) | Q8_0 | 15.8 | fast, best quality | 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.