gguf arxiv:2311.03099 arxiv:2306.01708 endpoints_compatible region:us
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---
Quantization made by Richard Erkhov.

[Github](https://github.com/RichardErkhov)

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MedLlama-3-8B_DARE - GGUF
- Model creator: https://huggingface.co/ChenWeiLi/
- Original model: https://huggingface.co/ChenWeiLi/MedLlama-3-8B_DARE/


| Name | Quant method | Size |
| ---- | ---- | ---- |
| [MedLlama-3-8B_DARE.Q2_K.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.Q2_K.gguf) | Q2_K | 2.96GB |
| [MedLlama-3-8B_DARE.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.IQ3_XS.gguf) | IQ3_XS | 3.28GB |
| [MedLlama-3-8B_DARE.IQ3_S.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.IQ3_S.gguf) | IQ3_S | 3.43GB |
| [MedLlama-3-8B_DARE.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.Q3_K_S.gguf) | Q3_K_S | 3.41GB |
| [MedLlama-3-8B_DARE.IQ3_M.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.IQ3_M.gguf) | IQ3_M | 3.52GB |
| [MedLlama-3-8B_DARE.Q3_K.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.Q3_K.gguf) | Q3_K | 3.74GB |
| [MedLlama-3-8B_DARE.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.Q3_K_M.gguf) | Q3_K_M | 3.74GB |
| [MedLlama-3-8B_DARE.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.Q3_K_L.gguf) | Q3_K_L | 4.03GB |
| [MedLlama-3-8B_DARE.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.IQ4_XS.gguf) | IQ4_XS | 4.18GB |
| [MedLlama-3-8B_DARE.Q4_0.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.Q4_0.gguf) | Q4_0 | 4.34GB |
| [MedLlama-3-8B_DARE.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.IQ4_NL.gguf) | IQ4_NL | 4.38GB |
| [MedLlama-3-8B_DARE.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.Q4_K_S.gguf) | Q4_K_S | 4.37GB |
| [MedLlama-3-8B_DARE.Q4_K.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.Q4_K.gguf) | Q4_K | 4.58GB |
| [MedLlama-3-8B_DARE.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.Q4_K_M.gguf) | Q4_K_M | 4.58GB |
| [MedLlama-3-8B_DARE.Q4_1.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.Q4_1.gguf) | Q4_1 | 4.78GB |
| [MedLlama-3-8B_DARE.Q5_0.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.Q5_0.gguf) | Q5_0 | 5.21GB |
| [MedLlama-3-8B_DARE.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.Q5_K_S.gguf) | Q5_K_S | 5.21GB |
| [MedLlama-3-8B_DARE.Q5_K.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.Q5_K.gguf) | Q5_K | 5.34GB |
| [MedLlama-3-8B_DARE.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.Q5_K_M.gguf) | Q5_K_M | 5.34GB |
| [MedLlama-3-8B_DARE.Q5_1.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.Q5_1.gguf) | Q5_1 | 5.65GB |
| [MedLlama-3-8B_DARE.Q6_K.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.Q6_K.gguf) | Q6_K | 6.14GB |
| [MedLlama-3-8B_DARE.Q8_0.gguf](https://huggingface.co/RichardErkhov/ChenWeiLi_-_MedLlama-3-8B_DARE-gguf/blob/main/MedLlama-3-8B_DARE.Q8_0.gguf) | Q8_0 | 7.95GB |




Original model description:
---
base_model:
- sethuiyer/Medichat-Llama3-8B
- mlabonne/ChimeraLlama-3-8B-v3
- johnsnowlabs/JSL-MedLlama-3-8B-v2.0
library_name: transformers
tags:
- mergekit
- merge
license: llama3
---
# medLlama-3-8B_DARE

This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).

## Merge Details
### Merge Method

This model was merged using the [DARE](https://arxiv.org/abs/2311.03099) [TIES](https://arxiv.org/abs/2306.01708) merge method using [mlabonne/ChimeraLlama-3-8B-v3](https://huggingface.co/mlabonne/ChimeraLlama-3-8B-v3) as a base.

### Models Merged

The following models were included in the merge:
* [sethuiyer/Medichat-Llama3-8B](https://huggingface.co/sethuiyer/Medichat-Llama3-8B)
* [johnsnowlabs/JSL-MedLlama-3-8B-v2.0](https://huggingface.co/johnsnowlabs/JSL-MedLlama-3-8B-v2.0)

### Evaluation

- multimedq (0 shot) </br>
  
|             Tasks             |Version|Filter|n-shot| Metric |Value |   |Stderr|
|-------------------------------|-------|------|-----:|--------|-----:|---|-----:|
| - medmcqa                     |Yaml   |none  |     0|acc     |0.5728|±  |0.0076|
|                               |       |none  |     0|acc_norm|0.5728|±  |0.0076|
| - medqa_4options              |Yaml   |none  |     0|acc     |0.5923|±  |0.0138|
|                               |       |none  |     0|acc_norm|0.5923|±  |0.0138|
| - anatomy (mmlu)              |      0|none  |     0|acc     |0.7111|±  |0.0392|
| - clinical_knowledge (mmlu)   |      0|none  |     0|acc     |0.7547|±  |0.0265|
| - college_biology (mmlu)      |      0|none  |     0|acc     |0.7917|±  |0.0340|
| - college_medicine (mmlu)     |      0|none  |     0|acc     |0.6647|±  |0.0360|
| - medical_genetics (mmlu)     |      0|none  |     0|acc     |0.8200|±  |0.0386|
| - professional_medicine (mmlu)|      0|none  |     0|acc     |0.7426|±  |0.0266|
|stem                           |N/A    |none  |     0|acc_norm|0.5773|±  |0.0067|
|                               |       |none  |     0|acc     |0.6145|±  |0.0057|
| - pubmedqa                    |      1|none  |     0|acc     |0.7400|±  |0.0196|

|Groups|Version|Filter|n-shot| Metric |Value |   |Stderr|
|------|-------|------|-----:|--------|-----:|---|-----:|
|stem  |N/A    |none  |     0|acc_norm|0.5773|±  |0.0067|
|      |       |none  |     0|acc     |0.6145|±  |0.0057|

### Configuration

The following YAML configuration was used to produce this model:

```yaml
models:
  - model: mlabonne/ChimeraLlama-3-8B-v3
    # No parameters necessary for base model

  - model: sethuiyer/Medichat-Llama3-8B
    parameters:
      density: 0.53
      weight: 0.5
  - model: johnsnowlabs/JSL-MedLlama-3-8B-v2.0
    parameters:
      density: 0.53
      weight: 0.5
      
merge_method: dare_ties
base_model: mlabonne/ChimeraLlama-3-8B-v3
parameters:
  int8_mask: true
dtype: float16

```

