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Model: prithivMLmods/Astral-4B-Preview-GGUF
Source: Original Platform

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README.md

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+---
+license: apache-2.0
+language:
+- en
+base_model:
+- LucidityAI/Astral-4B-Preview
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- text-generation-inference
+---
+
+# **Astral-4B-Preview-GGUF**
+
+> Astral-4B-Preview is a reasoning-centric language model from the Astral series, built on Qwen3-4b-thinking-2507 and fine-tuned on the nvidia/AceReason-1.1-SFT dataset to deliver configurable, step-by-step logical reasoning for research and development use. By including a "Reasoning-level" directive in the system prompt, users can control the model’s depth of reasoning—from direct answers to ultra-detailed reasoning traces—enabling nuanced, structured responses tailored to diverse problem-solving needs. As a preview release, Astral-4B-Preview is ideal for evaluating advanced reasoning capabilities with user-guided depth control in scientific and technical tasks.
+
+## Model Files
+
+| File Name | Quant Type | File Size |
+| - | - | - |
+| Astral-4B-Preview.BF16.gguf | BF16 | 8.05 GB |
+| Astral-4B-Preview.F16.gguf | F16 | 8.05 GB |
+| Astral-4B-Preview.F32.gguf | F32 | 16.1 GB |
+| Astral-4B-Preview.Q2_K.gguf | Q2_K | 1.67 GB |
+| Astral-4B-Preview.Q3_K_L.gguf | Q3_K_L | 2.24 GB |
+| Astral-4B-Preview.Q3_K_M.gguf | Q3_K_M | 2.08 GB |
+| Astral-4B-Preview.Q3_K_S.gguf | Q3_K_S | 1.89 GB |
+| Astral-4B-Preview.Q4_K_M.gguf | Q4_K_M | 2.5 GB |
+| Astral-4B-Preview.Q4_K_S.gguf | Q4_K_S | 2.38 GB |
+| Astral-4B-Preview.Q5_K_M.gguf | Q5_K_M | 2.89 GB |
+| Astral-4B-Preview.Q5_K_S.gguf | Q5_K_S | 2.82 GB |
+| Astral-4B-Preview.Q6_K.gguf | Q6_K | 3.31 GB |
+| Astral-4B-Preview.Q8_0.gguf | Q8_0 | 4.28 GB |
+
+## Quants Usage 
+
+(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)
+
+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)

config.json

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+{
+    "model_type": "qwen3"
+}

configuration.json

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+{"framework": "pytorch", "task": "text-generation", "allow_remote": true}