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  <!-- ### quantize_version: 2 -->
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  <!-- ### output_tensor_quantised: 1 -->
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  <!-- ### convert_type: hf -->
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  <!-- ### quants_skip: -->
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  <!-- ### skip_mmproj: -->
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  static quants of https://huggingface.co/DavidAU/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ base_model: DavidAU/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B
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+ datasets:
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+ - sequelbox/Celestia3-DeepSeek-R1-0528
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+ - sequelbox/Mitakihara-DeepSeek-R1-0528
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+ - sequelbox/Raiden-DeepSeek-R1
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+ language:
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+ - en
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+ library_name: transformers
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+ license: apache-2.0
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+ mradermacher:
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+ readme_rev: 1
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+ quantized_by: mradermacher
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+ tags:
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+ - merge
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+ - programming
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+ - code generation
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+ - code
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+ - coding
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+ - coder
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+ - chat
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+ - code
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+ - chat
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+ - qwen
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+ - qwen3
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+ - qwencoder
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+ - esper
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+ - esper-3
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+ - valiant
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+ - valiant-labs
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+ - qwen
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+ - qwen-3
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+ - qwen-3-2.4b
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+ - 2.4b
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+ - reasoning
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+ - code
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+ - code-instruct
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+ - python
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+ - javascript
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+ - dev-ops
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+ - jenkins
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+ - terraform
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+ - scripting
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+ - powershell
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+ - azure
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+ - aws
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+ - gcp
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+ - cloud
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+ - problem-solving
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+ - architect
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+ - engineer
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+ - developer
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+ - creative
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+ - analytical
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+ - expert
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+ - rationality
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+ - conversational
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+ - chat
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+ - instruct
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+ - shining-valiant
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+ - shining-valiant-3
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+ - valiant
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+ - valiant-labs
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+ - qwen
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+ - qwen-3
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+ - qwen-3-1.7b
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+ - 1.7b
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+ - reasoning
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+ - code
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+ - code-reasoning
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+ - science
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+ - science-reasoning
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+ - physics
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+ - biology
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+ - chemistry
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+ - earth-science
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+ - astronomy
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+ - machine-learning
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+ - artificial-intelligence
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+ - compsci
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+ - computer-science
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+ - information-theory
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+ - ML-Ops
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+ - math
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+ - cuda
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+ - deep-learning
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+ - transformers
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+ - agentic
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+ - LLM
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+ - neuromorphic
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+ - self-improvement
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+ - complex-systems
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+ - cognition
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+ - linguistics
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+ - philosophy
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+ - logic
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+ - epistemology
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+ - simulation
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+ - game-theory
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+ - knowledge-management
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+ - creativity
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+ - problem-solving
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+ - architect
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+ - engineer
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+ - developer
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+ - creative
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+ - analytical
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+ - expert
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+ - rationality
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+ - conversational
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+ - chat
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+ - instruct
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+ - float32
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+ ---
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+ ## About
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+
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  <!-- ### quantize_version: 2 -->
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  <!-- ### output_tensor_quantised: 1 -->
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  <!-- ### convert_type: hf -->
 
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  <!-- ### quants_skip: -->
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  <!-- ### skip_mmproj: -->
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  static quants of https://huggingface.co/DavidAU/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B
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+
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+ <!-- provided-files -->
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+
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+ ***For a convenient overview and download list, visit our [model page for this model](https://hf.tst.eu/model#Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B-GGUF).***
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+
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+ weighted/imatrix quants are available at https://huggingface.co/mradermacher/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B-i1-GGUF
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+ ## Usage
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+
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+ If you are unsure how to use GGUF files, refer to one of [TheBloke's
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+ READMEs](https://huggingface.co/TheBloke/KafkaLM-70B-German-V0.1-GGUF) for
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+ more details, including on how to concatenate multi-part files.
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+
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+ ## Provided Quants
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+
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+ (sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
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+
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+ | Link | Type | Size/GB | Notes |
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+ |:-----|:-----|--------:|:------|
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B-GGUF/resolve/main/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B.Q2_K.gguf) | Q2_K | 1.2 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B-GGUF/resolve/main/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B.Q3_K_S.gguf) | Q3_K_S | 1.4 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B-GGUF/resolve/main/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B.Q3_K_M.gguf) | Q3_K_M | 1.5 | lower quality |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B-GGUF/resolve/main/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B.Q3_K_L.gguf) | Q3_K_L | 1.6 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B-GGUF/resolve/main/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B.IQ4_XS.gguf) | IQ4_XS | 1.7 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B-GGUF/resolve/main/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B.Q4_K_S.gguf) | Q4_K_S | 1.7 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B-GGUF/resolve/main/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B.Q4_K_M.gguf) | Q4_K_M | 1.8 | fast, recommended |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B-GGUF/resolve/main/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B.Q5_K_S.gguf) | Q5_K_S | 2.0 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B-GGUF/resolve/main/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B.Q5_K_M.gguf) | Q5_K_M | 2.1 | |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B-GGUF/resolve/main/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B.Q6_K.gguf) | Q6_K | 2.4 | very good quality |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B-GGUF/resolve/main/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B.Q8_0.gguf) | Q8_0 | 3.0 | fast, best quality |
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+ | [GGUF](https://huggingface.co/mradermacher/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B-GGUF/resolve/main/Qwen3-Shining-Valiant-Instruct-CODER-Reasoning-2.7B.f16.gguf) | f16 | 5.6 | 16 bpw, overkill |
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+
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+ Here is a handy graph by ikawrakow comparing some lower-quality quant
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+ types (lower is better):
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+
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+ ![image.png](https://www.nethype.de/huggingface_embed/quantpplgraph.png)
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+
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+ And here are Artefact2's thoughts on the matter:
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+ https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
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+
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+ ## FAQ / Model Request
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+
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+ See https://huggingface.co/mradermacher/model_requests for some answers to
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+ questions you might have and/or if you want some other model quantized.
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+
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+ ## Thanks
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+
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+ I thank my company, [nethype GmbH](https://www.nethype.de/), for letting
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+ me use its servers and providing upgrades to my workstation to enable
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+ this work in my free time.
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+
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+ <!-- end -->