Instructions to use nokissgoodbye/diffusion_libero10 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- LeRobot
How to use nokissgoodbye/diffusion_libero10 with LeRobot:
- Notebooks
- Google Colab
- Kaggle
Upload policy weights, train config and readme
Browse files- README.md +1 -1
- model.safetensors +1 -1
- train_config.json +3 -3
README.md
CHANGED
|
@@ -5,8 +5,8 @@ license: apache-2.0
|
|
| 5 |
model_name: diffusion
|
| 6 |
pipeline_tag: robotics
|
| 7 |
tags:
|
| 8 |
-
- lerobot
|
| 9 |
- robotics
|
|
|
|
| 10 |
- diffusion
|
| 11 |
---
|
| 12 |
|
|
|
|
| 5 |
model_name: diffusion
|
| 6 |
pipeline_tag: robotics
|
| 7 |
tags:
|
|
|
|
| 8 |
- robotics
|
| 9 |
+
- lerobot
|
| 10 |
- diffusion
|
| 11 |
---
|
| 12 |
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 1111877924
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:66562ce5aedc6af8467229e826303c3f90a280575b20dc68d8c59c4340ce36f7
|
| 3 |
size 1111877924
|
train_config.json
CHANGED
|
@@ -270,16 +270,16 @@
|
|
| 270 |
"scheduler_warmup_steps": 500
|
| 271 |
},
|
| 272 |
"reward_model": null,
|
| 273 |
-
"output_dir": "outputs/train/
|
| 274 |
"job_name": "libero_diffusion",
|
| 275 |
"resume": false,
|
| 276 |
"seed": 1000,
|
| 277 |
"cudnn_deterministic": false,
|
| 278 |
"num_workers": 4,
|
| 279 |
-
"batch_size":
|
| 280 |
"prefetch_factor": 4,
|
| 281 |
"persistent_workers": true,
|
| 282 |
-
"steps":
|
| 283 |
"eval_freq": 0,
|
| 284 |
"log_freq": 200,
|
| 285 |
"tolerance_s": 0.0001,
|
|
|
|
| 270 |
"scheduler_warmup_steps": 500
|
| 271 |
},
|
| 272 |
"reward_model": null,
|
| 273 |
+
"output_dir": "outputs/train/diffusion_libero10_v3",
|
| 274 |
"job_name": "libero_diffusion",
|
| 275 |
"resume": false,
|
| 276 |
"seed": 1000,
|
| 277 |
"cudnn_deterministic": false,
|
| 278 |
"num_workers": 4,
|
| 279 |
+
"batch_size": 32,
|
| 280 |
"prefetch_factor": 4,
|
| 281 |
"persistent_workers": true,
|
| 282 |
+
"steps": 200000,
|
| 283 |
"eval_freq": 0,
|
| 284 |
"log_freq": 200,
|
| 285 |
"tolerance_s": 0.0001,
|