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Echelon-AI_-_Med-Qwen2-7B-gguf
RichardErkhov/Echelon-AI_-_Med-Qwen2-7B-gguf
Echelon-AI_-_Med-Qwen2-7B-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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.gguf102 GB · 100%
At a glance
- Access
- Public
- Created
- Sep 20, 2024
- Updated
- Sep 20, 2024
- SHA
- 8d5dd4d2
Model card
From the Hugging Face model README
Quantization made by Richard Erkhov.
Med-Qwen2-7B - GGUF
- Model creator: https://huggingface.co/Echelon-AI/
- Original model: https://huggingface.co/Echelon-AI/Med-Qwen2-7B/
| Name | Quant method | Size |
|---|---|---|
| Med-Qwen2-7B.Q2_K.gguf | Q2_K | 2.81GB |
| Med-Qwen2-7B.IQ3_XS.gguf | IQ3_XS | 3.12GB |
| Med-Qwen2-7B.IQ3_S.gguf | IQ3_S | 3.26GB |
| Med-Qwen2-7B.Q3_K_S.gguf | Q3_K_S | 3.25GB |
| Med-Qwen2-7B.IQ3_M.gguf | IQ3_M | 3.33GB |
| Med-Qwen2-7B.Q3_K.gguf | Q3_K | 3.55GB |
| Med-Qwen2-7B.Q3_K_M.gguf | Q3_K_M | 3.55GB |
| Med-Qwen2-7B.Q3_K_L.gguf | Q3_K_L | 3.81GB |
| Med-Qwen2-7B.IQ4_XS.gguf | IQ4_XS | 3.96GB |
| Med-Qwen2-7B.Q4_0.gguf | Q4_0 | 4.13GB |
| Med-Qwen2-7B.IQ4_NL.gguf | IQ4_NL | 4.16GB |
| Med-Qwen2-7B.Q4_K_S.gguf | Q4_K_S | 4.15GB |
| Med-Qwen2-7B.Q4_K.gguf | Q4_K | 4.36GB |
| Med-Qwen2-7B.Q4_K_M.gguf | Q4_K_M | 4.36GB |
| Med-Qwen2-7B.Q4_1.gguf | Q4_1 | 4.54GB |
| Med-Qwen2-7B.Q5_0.gguf | Q5_0 | 4.95GB |
| Med-Qwen2-7B.Q5_K_S.gguf | Q5_K_S | 4.95GB |
| Med-Qwen2-7B.Q5_K.gguf | Q5_K | 5.07GB |
| Med-Qwen2-7B.Q5_K_M.gguf | Q5_K_M | 5.07GB |
| Med-Qwen2-7B.Q5_1.gguf | Q5_1 | 5.36GB |
| Med-Qwen2-7B.Q6_K.gguf | Q6_K | 5.82GB |
| Med-Qwen2-7B.Q8_0.gguf | Q8_0 | 7.54GB |
Original model description:
license: apache-2.0 datasets:
- Malikeh1375/medical-question-answering-datasets
Qwen2 7B, after finetuning on a medical dataset, demonstrates enhanced performance in medical text understanding and generation
Model Description
The model shows improved accuracy in diagnosing medical conditions, generating specialized medical texts, and responding to medical queries with contextually relevant information. This adaptation equips Med-Qwen2 to support advanced applications in healthcare, offering nuanced insights and precise language processing tailored for medical professionals and patients alike
- Finetuned from model : https://huggingface.co/Qwen/Qwen2-7B-Instruct
Uses
- Diagnosing medical conditions with improved accuracy.
- Generating specialized medical texts and reports.
- Providing contextually relevant responses to medical queries.
- Supporting advanced applications in healthcare with precise language processing.
- Created
- Sep 20, 2024
- Updated
- Sep 20, 2024