gguf endpoints_compatible region:us
---
{}
---
Quantization made by Richard Erkhov.

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

[Discord](https://discord.gg/pvy7H8DZMG)

[Request more models](https://github.com/RichardErkhov/quant_request)


MedGPT-Gemma2-9B-BA-v.1 - GGUF
- Model creator: https://huggingface.co/valeriojob/
- Original model: https://huggingface.co/valeriojob/MedGPT-Gemma2-9B-BA-v.1/


| Name | Quant method | Size |
| ---- | ---- | ---- |
| [MedGPT-Gemma2-9B-BA-v.1.Q2_K.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.Q2_K.gguf) | Q2_K | 3.54GB |
| [MedGPT-Gemma2-9B-BA-v.1.IQ3_XS.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.IQ3_XS.gguf) | IQ3_XS | 3.86GB |
| [MedGPT-Gemma2-9B-BA-v.1.IQ3_S.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.IQ3_S.gguf) | IQ3_S | 4.04GB |
| [MedGPT-Gemma2-9B-BA-v.1.Q3_K_S.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.Q3_K_S.gguf) | Q3_K_S | 4.04GB |
| [MedGPT-Gemma2-9B-BA-v.1.IQ3_M.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.IQ3_M.gguf) | IQ3_M | 4.19GB |
| [MedGPT-Gemma2-9B-BA-v.1.Q3_K.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.Q3_K.gguf) | Q3_K | 4.43GB |
| [MedGPT-Gemma2-9B-BA-v.1.Q3_K_M.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.Q3_K_M.gguf) | Q3_K_M | 4.43GB |
| [MedGPT-Gemma2-9B-BA-v.1.Q3_K_L.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.Q3_K_L.gguf) | Q3_K_L | 4.78GB |
| [MedGPT-Gemma2-9B-BA-v.1.IQ4_XS.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.IQ4_XS.gguf) | IQ4_XS | 4.86GB |
| [MedGPT-Gemma2-9B-BA-v.1.Q4_0.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.Q4_0.gguf) | Q4_0 | 5.07GB |
| [MedGPT-Gemma2-9B-BA-v.1.IQ4_NL.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.IQ4_NL.gguf) | IQ4_NL | 5.1GB |
| [MedGPT-Gemma2-9B-BA-v.1.Q4_K_S.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.Q4_K_S.gguf) | Q4_K_S | 5.1GB |
| [MedGPT-Gemma2-9B-BA-v.1.Q4_K.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.Q4_K.gguf) | Q4_K | 5.37GB |
| [MedGPT-Gemma2-9B-BA-v.1.Q4_K_M.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.Q4_K_M.gguf) | Q4_K_M | 5.37GB |
| [MedGPT-Gemma2-9B-BA-v.1.Q4_1.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.Q4_1.gguf) | Q4_1 | 5.55GB |
| [MedGPT-Gemma2-9B-BA-v.1.Q5_0.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.Q5_0.gguf) | Q5_0 | 6.04GB |
| [MedGPT-Gemma2-9B-BA-v.1.Q5_K_S.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.Q5_K_S.gguf) | Q5_K_S | 6.04GB |
| [MedGPT-Gemma2-9B-BA-v.1.Q5_K.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.Q5_K.gguf) | Q5_K | 6.19GB |
| [MedGPT-Gemma2-9B-BA-v.1.Q5_K_M.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.Q5_K_M.gguf) | Q5_K_M | 6.19GB |
| [MedGPT-Gemma2-9B-BA-v.1.Q5_1.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.Q5_1.gguf) | Q5_1 | 6.52GB |
| [MedGPT-Gemma2-9B-BA-v.1.Q6_K.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.Q6_K.gguf) | Q6_K | 7.07GB |
| [MedGPT-Gemma2-9B-BA-v.1.Q8_0.gguf](https://huggingface.co/RichardErkhov/valeriojob_-_MedGPT-Gemma2-9B-BA-v.1-gguf/blob/main/MedGPT-Gemma2-9B-BA-v.1.Q8_0.gguf) | Q8_0 | 9.15GB |




Original model description:
---
base_model: unsloth/gemma-2-9b
language:
- en
license: apache-2.0
tags:
- text-generation-inference
- transformers
- unsloth
- llama
- trl
- sft
---

# MedGPT-Gemma2-9B-v.1

- This model is a fine-tuned version of [unsloth/gemma-2-9b](https://huggingface.co/unsloth/gemma-2-9b) on an dataset created by [Valerio Job](https://huggingface.co/valeriojob) together with GPs based on real medical data.
- Version 1 (v.1) of MedGPT is the very first version of MedGPT and the training dataset has been kept simple and small with only 60 examples.
- This repo includes the 16bit format of the model as well as the LoRA adapters of the model. There is a separate repo called [valeriojob/MedGPT-Gemma2-9B-BA-v.1-GGUF](https://huggingface.co/valeriojob/MedGPT-Gemma2-9B-BA-v.1-GGUF) that includes the quantized versions of this model in GGUF format.
- This model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.

## Model description

This model acts as a supplementary assistance to GPs helping them in medical and admin tasks.

## Intended uses & limitations

The fine-tuned model should not be used in production! This model has been created as a initial prototype in the context of a bachelor thesis.

## Training and evaluation data

The dataset (train and test) used for fine-tuning this model can be found here: [datasets/valeriojob/BA-v.1](https://huggingface.co/datasets/valeriojob/BA-v.1)

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- per_device_train_batch_size = 2,
- gradient_accumulation_steps = 4,
- warmup_steps = 5,
- max_steps = 60,
- learning_rate = 2e-4,
- fp16 = not is_bfloat16_supported(),
- bf16 = is_bfloat16_supported(),
- logging_steps = 1,
- optim = "adamw_8bit",
- weight_decay = 0.01,
- lr_scheduler_type = "linear",
- seed = 3407,
- output_dir = "outputs"

### Training results

| Training Loss | Step |
|:-------------:|:----:|
| 2.237900      | 1    |
| 2.292200      | 2    |
| 2.215200      | 3    |
| 1.561200      | 5    |
| 0.584500      | 10   |
| 0.372500      | 15   |
| 0.258600      | 20   |
| 0.126300      | 30   |
| 0.064100      | 40   |
| 0.040800      | 50   |
| 0.045700      | 60   |

## Licenses
- **License:** apache-2.0

