End of training

.gitattributes

@@ -33,3 +33,7 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+image_0.png filter=lfs diff=lfs merge=lfs -text
+image_1.png filter=lfs diff=lfs merge=lfs -text
+image_2.png filter=lfs diff=lfs merge=lfs -text
+image_3.png filter=lfs diff=lfs merge=lfs -text

10_lora.pt

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0e336dc9664c5c97c4a9bbe856f5f2f7d5a8a17e98326aefc2abf1bb0b0c33fe
+size 888651

10_lora_config.json

@@ -0,0 +1 @@
+{"peft_config": {"task_type": null, "peft_type": "LORA", "auto_mapping": null, "peft_version": "0.19.1", "base_model_name_or_path": null, "revision": null, "inference_mode": false, "r": 4, "target_modules": ["query", "to_v", "to_q", "value"], "exclude_modules": null, "lora_alpha": 4, "lora_dropout": 0.0, "fan_in_fan_out": false, "bias": "none", "use_rslora": false, "modules_to_save": null, "init_lora_weights": true, "layers_to_transform": null, "layers_pattern": null, "rank_pattern": {}, "alpha_pattern": {}, "megatron_config": null, "megatron_core": "megatron.core", "trainable_token_indices": null, "loftq_config": {}, "eva_config": null, "corda_config": null, "lora_ga_config": null, "use_dora": false, "alora_invocation_tokens": null, "use_qalora": false, "qalora_group_size": 16, "layer_replication": null, "lora_bias": false, "target_parameters": null, "use_bdlora": null, "arrow_config": null, "ensure_weight_tying": false}}

README.md

@@ -0,0 +1,21 @@
+
+---
+license: creativeml-openrail-m
+base_model: segmind/tiny-sd
+tags:
+- stable-diffusion
+- stable-diffusion-diffusers
+- text-to-image
+- diffusers
+- lora
+inference: true
+---
+    
+# LoRA text2image fine-tuning - TeddyVDobreva/lora-output
+These are LoRA adaption weights for segmind/tiny-sd. The weights were fine-tuned on the None dataset. You can find some example images in the following. 
+
+![img_0](./image_0.png)
+![img_1](./image_1.png)
+![img_2](./image_2.png)
+![img_3](./image_3.png)
+