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Model: prithivMLmods/MedScholar-1.5B-f32-GGUF
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2026-08-11 14:25:13 +08:00
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---
license: apache-2.0
base_model:
- yasserrmd/MedScholar-1.5B
language:
- en
pipeline_tag: text-generation
library_name: transformers
tags:
- text-generation-inference
---
# **MedScholar-1.5B-f32-GGUF**
> MedScholar-1.5B is a compact, instruction-aligned medical question-answering model based on Qwen2.5-1.5B-Instruct, fine-tuned using 1 million samples from the MIRIAD-4.4M dataset, and designed for research and educational exploration of clinical knowledge, not for diagnosis or medical decision-making. The model is trained using the Unsloth framework and QLoRA, employs a minimal QA prompt format, and operates under the Apache-2.0 and ODC-By 1.0 licenses; it is strictly intended for non-clinical, academic use only, with output not to be used for real patient care or advice.
## Model Files
| File name | Size | Quant Type |
|-----------|------|------------|
| MedScholar-1.5B.F32.gguf | 6.18 GB | F32 |
| MedScholar-1.5B.BF16.gguf | 3.09 GB | BF16 |
| MedScholar-1.5B.F16.gguf | 3.09 GB | F16 |
| MedScholar-1.5B.Q8_0.gguf | 1.65 GB | Q8_0 |
| MedScholar-1.5B.Q6_K.gguf | 1.27 GB | Q6_K |
| MedScholar-1.5B.Q5_K_M.gguf | 1.13 GB | Q5_K_M |
| MedScholar-1.5B.Q5_K_S.gguf | 1.1 GB | Q5_K_S |
| MedScholar-1.5B.Q4_K_M.gguf | 986 MB | Q4_K_M |
| MedScholar-1.5B.Q4_K_S.gguf | 940 MB | Q4_K_S |
| MedScholar-1.5B.Q3_K_L.gguf | 880 MB | Q3_K_L |
| MedScholar-1.5B.Q3_K_M.gguf | 824 MB | Q3_K_M |
| MedScholar-1.5B.Q3_K_S.gguf | 761 MB | Q3_K_S |
| MedScholar-1.5B.Q2_K.gguf | 676 MB | Q2_K |
## 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)

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{
"model_type": "qwen2"
}

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