End of training

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---
license: creativeml-openrail-m
library_name: diffusers
tags:
- stable-diffusion
- stable-diffusion-diffusers
- text-to-image
- diffusers
- diffusers-training
- lora
base_model: runwayml/stable-diffusion-v1-5
inference: true
---
<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->


    # LoRA text2image fine-tuning - PQlet/lora-narutoblip-debug-r128-a16
    These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the Naruto-BLIP dataset. You can find some example images in the following. 
![img_0](./image_a_man_with_glasses_and_a_shirt_on.png)
![img_1](./image_a_group_of_people_sitting_on_the_ground.png)
![img_2](./image_a_man_in_a_green_hoodie_standing_in_front_of_a_mountain.png)
![img_3](./image_a_man_with_a_gun_in_his_hand.png)
![img_4](./image_a_woman_with_red_hair_and_a_cat_on_her_head.png)
![img_5](./image_two_pokemons_sitting_on_top_of_a_cloud.png)
![img_6](./image_a_man_standing_in_front_of_a_bridge.png)

## Intended uses & limitations

#### How to use

```python
# TODO: add an example code snippet for running this diffusion pipeline
```

#### Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

## Training details

[TODO: describe the data used to train the model]

	---
	license: creativeml-openrail-m
	library_name: diffusers
	tags:
	- stable-diffusion
	- stable-diffusion-diffusers
	- text-to-image
	- diffusers
	- diffusers-training
	- lora
	base_model: runwayml/stable-diffusion-v1-5
	inference: true
	---

	<!-- This model card has been generated automatically according to the information the training script had access to. You
	should probably proofread and complete it, then remove this comment. -->


	# LoRA text2image fine-tuning - PQlet/lora-narutoblip-debug-r128-a16
	These are LoRA adaption weights for runwayml/stable-diffusion-v1-5. The weights were fine-tuned on the Naruto-BLIP dataset. You can find some example images in the following.
	![img_0](./image_a_man_with_glasses_and_a_shirt_on.png)
	![img_1](./image_a_group_of_people_sitting_on_the_ground.png)
	![img_2](./image_a_man_in_a_green_hoodie_standing_in_front_of_a_mountain.png)
	![img_3](./image_a_man_with_a_gun_in_his_hand.png)
	![img_4](./image_a_woman_with_red_hair_and_a_cat_on_her_head.png)
	![img_5](./image_two_pokemons_sitting_on_top_of_a_cloud.png)
	![img_6](./image_a_man_standing_in_front_of_a_bridge.png)


	## Intended uses & limitations

	#### How to use

	```python
	# TODO: add an example code snippet for running this diffusion pipeline
	```

	#### Limitations and bias

	[TODO: provide examples of latent issues and potential remediations]

	## Training details

	[TODO: describe the data used to train the model]