The following values were not passed to `accelerate launch` and had defaults used instead:
	`--dynamo_backend` was set to a value of `'no'`
To avoid this warning pass in values for each of the problematic parameters or run `accelerate config`.
A matching Triton is not available, some optimizations will not be enabled.
Error caught was: No module named 'triton'
09/05/2023 22:46:04 - INFO - __main__ - Distributed environment: MULTI_GPU  Backend: nccl
Num processes: 1
Process index: 0
Local process index: 0
Device: cuda:0

Mixed precision type: fp16

You are using a model of type clip_text_model to instantiate a model of type . This is not supported for all configurations of models and can yield errors.
You are using a model of type clip_text_model to instantiate a model of type . This is not supported for all configurations of models and can yield errors.
{'attention_type'} was not found in config. Values will be initialized to default values.
09/05/2023 22:46:17 - INFO - __main__ - Initializing t2iadapter weights from unet
Some weights of the model checkpoint at openai/clip-vit-large-patch14 were not used when initializing CLIPVisionModel: ['text_model.encoder.layers.7.self_attn.v_proj.bias', 'text_model.encoder.layers.4.self_attn.k_proj.bias', 'text_model.encoder.layers.4.self_attn.q_proj.bias', 'text_model.encoder.layers.6.mlp.fc2.bias', 'text_model.encoder.layers.2.self_attn.v_proj.weight', 'text_model.encoder.layers.11.mlp.fc1.bias', 'text_model.encoder.layers.7.self_attn.k_proj.bias', 'text_model.encoder.layers.3.self_attn.out_proj.weight', 'text_model.encoder.layers.3.mlp.fc1.weight', 'text_model.encoder.layers.2.layer_norm2.bias', 'text_model.encoder.layers.1.mlp.fc1.weight', 'text_model.encoder.layers.0.layer_norm1.weight', 'text_model.encoder.layers.4.self_attn.v_proj.bias', 'text_model.encoder.layers.0.self_attn.out_proj.bias', 'text_model.encoder.layers.1.self_attn.out_proj.bias', 'text_model.encoder.layers.8.self_attn.q_proj.bias', 'text_model.encoder.layers.7.mlp.fc2.weight', 'text_model.encoder.layers.8.self_attn.v_proj.weight', 'text_model.encoder.layers.0.self_attn.v_proj.weight', 'text_model.encoder.layers.6.self_attn.v_proj.bias', 'text_model.encoder.layers.1.mlp.fc1.bias', 'text_model.encoder.layers.0.layer_norm1.bias', 'text_model.encoder.layers.5.self_attn.k_proj.bias', 'text_model.encoder.layers.10.mlp.fc1.bias', 'text_model.encoder.layers.10.layer_norm2.weight', 'text_model.encoder.layers.10.layer_norm1.bias', 'text_model.encoder.layers.5.layer_norm2.weight', 'text_model.encoder.layers.0.mlp.fc2.bias', 'text_model.encoder.layers.3.self_attn.k_proj.weight', 'text_model.encoder.layers.4.layer_norm2.weight', 'text_model.encoder.layers.1.mlp.fc2.weight', 'text_model.encoder.layers.6.self_attn.k_proj.weight', 'text_model.encoder.layers.4.self_attn.q_proj.weight', 'text_model.encoder.layers.8.layer_norm1.bias', 'text_model.encoder.layers.2.self_attn.k_proj.weight', 'text_model.encoder.layers.3.self_attn.q_proj.weight', 'text_model.encoder.layers.6.self_attn.q_proj.weight', 'text_model.encoder.layers.8.layer_norm2.bias', 'text_model.encoder.layers.3.mlp.fc2.bias', 'text_model.encoder.layers.9.self_attn.out_proj.weight', 'text_model.encoder.layers.9.self_attn.v_proj.weight', 'text_model.final_layer_norm.weight', 'text_model.encoder.layers.6.self_attn.v_proj.weight', 'text_model.encoder.layers.2.self_attn.out_proj.bias', 'text_model.encoder.layers.4.layer_norm2.bias', 'text_model.encoder.layers.9.mlp.fc1.bias', 'text_model.encoder.layers.0.self_attn.q_proj.bias', 'text_model.encoder.layers.11.self_attn.q_proj.bias', 'text_model.encoder.layers.11.self_attn.q_proj.weight', 'text_model.encoder.layers.2.mlp.fc1.bias', 'text_model.encoder.layers.5.self_attn.out_proj.bias', 'text_model.encoder.layers.5.self_attn.v_proj.bias', 'text_model.encoder.layers.7.mlp.fc2.bias', 'text_model.encoder.layers.10.self_attn.k_proj.weight', 'text_model.encoder.layers.7.self_attn.out_proj.bias', 'text_model.encoder.layers.7.layer_norm1.bias', 'text_model.embeddings.token_embedding.weight', 'text_model.encoder.layers.6.mlp.fc1.weight', 'text_model.embeddings.position_embedding.weight', 'text_model.encoder.layers.10.self_attn.v_proj.weight', 'text_model.encoder.layers.10.self_attn.k_proj.bias', 'text_model.encoder.layers.3.layer_norm2.bias', 'text_model.encoder.layers.4.self_attn.v_proj.weight', 'text_model.encoder.layers.4.mlp.fc1.bias', 'text_model.encoder.layers.2.mlp.fc2.weight', 'text_model.encoder.layers.0.layer_norm2.bias', 'text_model.encoder.layers.10.mlp.fc2.weight', 'text_model.encoder.layers.4.mlp.fc1.weight', 'text_model.encoder.layers.2.layer_norm1.weight', 'text_model.encoder.layers.9.self_attn.q_proj.bias', 'text_model.encoder.layers.1.layer_norm2.weight', 'text_model.encoder.layers.8.self_attn.out_proj.bias', 'text_model.encoder.layers.1.mlp.fc2.bias', 'text_model.encoder.layers.10.mlp.fc1.weight', 'text_model.encoder.layers.11.layer_norm1.bias', 'text_model.encoder.layers.4.self_attn.k_proj.weight', 'text_model.encoder.layers.4.mlp.fc2.weight', 'text_model.encoder.layers.10.self_attn.v_proj.bias', 'text_model.encoder.layers.9.layer_norm2.bias', 'text_model.encoder.layers.11.mlp.fc1.weight', 'text_model.encoder.layers.7.self_attn.k_proj.weight', 'text_model.encoder.layers.5.layer_norm2.bias', 'text_model.encoder.layers.1.self_attn.q_proj.bias', 'text_model.encoder.layers.7.mlp.fc1.bias', 'text_model.encoder.layers.5.self_attn.q_proj.weight', 'text_model.encoder.layers.11.layer_norm1.weight', 'text_model.encoder.layers.10.layer_norm2.bias', 'text_model.encoder.layers.1.self_attn.v_proj.weight', 'text_model.encoder.layers.11.self_attn.k_proj.bias', 'text_model.encoder.layers.9.mlp.fc2.bias', 'text_model.encoder.layers.8.self_attn.k_proj.bias', 'text_model.encoder.layers.9.layer_norm1.bias', 'text_model.encoder.layers.3.layer_norm1.weight', 'text_model.encoder.layers.4.layer_norm1.bias', 'text_model.encoder.layers.2.layer_norm2.weight', 'text_model.encoder.layers.0.self_attn.k_proj.weight', 'text_model.encoder.layers.7.layer_norm2.bias', 'text_model.encoder.layers.7.self_attn.q_proj.bias', 'text_model.encoder.layers.9.self_attn.k_proj.weight', 'text_model.encoder.layers.7.layer_norm2.weight', 'text_model.encoder.layers.5.mlp.fc2.bias', 'text_model.encoder.layers.2.layer_norm1.bias', 'text_model.encoder.layers.7.self_attn.v_proj.weight', 'text_model.encoder.layers.10.self_attn.q_proj.weight', 'text_model.encoder.layers.8.self_attn.out_proj.weight', 'text_model.encoder.layers.5.layer_norm1.bias', 'text_model.encoder.layers.3.self_attn.k_proj.bias', 'text_model.final_layer_norm.bias', 'text_model.encoder.layers.11.mlp.fc2.weight', 'text_model.encoder.layers.3.self_attn.v_proj.bias', 'text_model.encoder.layers.7.self_attn.q_proj.weight', 'text_model.encoder.layers.3.mlp.fc2.weight', 'text_model.encoder.layers.6.layer_norm2.weight', 'text_model.encoder.layers.5.mlp.fc2.weight', 'text_model.encoder.layers.9.mlp.fc2.weight', 'text_model.encoder.layers.5.self_attn.v_proj.weight', 'text_model.encoder.layers.11.self_attn.v_proj.bias', 'text_model.encoder.layers.3.self_attn.out_proj.bias', 'text_model.encoder.layers.11.self_attn.out_proj.bias', 'text_model.encoder.layers.9.self_attn.q_proj.weight', 'text_model.encoder.layers.10.self_attn.q_proj.bias', 'text_model.encoder.layers.3.self_attn.v_proj.weight', 'text_model.encoder.layers.4.layer_norm1.weight', 'text_model.encoder.layers.9.self_attn.k_proj.bias', 'text_model.encoder.layers.10.self_attn.out_proj.bias', 'text_model.encoder.layers.6.layer_norm2.bias', 'text_model.encoder.layers.7.self_attn.out_proj.weight', 'text_model.encoder.layers.2.mlp.fc1.weight', 'text_model.encoder.layers.5.self_attn.out_proj.weight', 'text_model.encoder.layers.8.mlp.fc1.weight', 'text_model.encoder.layers.8.self_attn.k_proj.weight', 'text_model.encoder.layers.6.self_attn.out_proj.bias', 'text_model.encoder.layers.5.layer_norm1.weight', 'text_model.encoder.layers.1.layer_norm2.bias', 'text_model.encoder.layers.2.self_attn.v_proj.bias', 'text_model.encoder.layers.10.mlp.fc2.bias', 'text_model.embeddings.position_ids', 'text_model.encoder.layers.11.self_attn.k_proj.weight', 'text_model.encoder.layers.3.layer_norm1.bias', 'text_model.encoder.layers.5.mlp.fc1.weight', 'text_model.encoder.layers.11.self_attn.out_proj.weight', 'text_model.encoder.layers.7.layer_norm1.weight', 'text_model.encoder.layers.3.layer_norm2.weight', 'text_model.encoder.layers.10.layer_norm1.weight', 'text_model.encoder.layers.8.mlp.fc1.bias', 'text_model.encoder.layers.0.layer_norm2.weight', 'text_model.encoder.layers.9.layer_norm2.weight', 'text_model.encoder.layers.0.mlp.fc1.weight', 'text_model.encoder.layers.2.self_attn.out_proj.weight', 'visual_projection.weight', 'text_model.encoder.layers.11.self_attn.v_proj.weight', 'text_model.encoder.layers.11.layer_norm2.bias', 'text_model.encoder.layers.1.self_attn.v_proj.bias', 'text_model.encoder.layers.9.mlp.fc1.weight', 'text_model.encoder.layers.8.mlp.fc2.weight', 'text_model.encoder.layers.1.self_attn.out_proj.weight', 'text_model.encoder.layers.2.self_attn.k_proj.bias', 'text_model.encoder.layers.8.layer_norm1.weight', 'text_model.encoder.layers.1.self_attn.q_proj.weight', 'text_model.encoder.layers.9.layer_norm1.weight', 'text_model.encoder.layers.4.self_attn.out_proj.bias', 'text_model.encoder.layers.6.layer_norm1.bias', 'text_model.encoder.layers.0.self_attn.v_proj.bias', 'text_model.encoder.layers.5.self_attn.k_proj.weight', 'text_model.encoder.layers.5.self_attn.q_proj.bias', 'text_model.encoder.layers.3.mlp.fc1.bias', 'text_model.encoder.layers.0.self_attn.q_proj.weight', 'text_model.encoder.layers.6.self_attn.k_proj.bias', 'text_model.encoder.layers.3.self_attn.q_proj.bias', 'text_model.encoder.layers.1.self_attn.k_proj.bias', 'text_model.encoder.layers.5.mlp.fc1.bias', 'text_model.encoder.layers.0.mlp.fc1.bias', 'text_model.encoder.layers.8.layer_norm2.weight', 'text_model.encoder.layers.0.self_attn.k_proj.bias', 'text_model.encoder.layers.6.self_attn.q_proj.bias', 'text_model.encoder.layers.1.layer_norm1.weight', 'text_model.encoder.layers.4.self_attn.out_proj.weight', 'text_projection.weight', 'text_model.encoder.layers.11.mlp.fc2.bias', 'text_model.encoder.layers.11.layer_norm2.weight', 'text_model.encoder.layers.8.self_attn.q_proj.weight', 'logit_scale', 'text_model.encoder.layers.7.mlp.fc1.weight', 'text_model.encoder.layers.9.self_attn.out_proj.bias', 'text_model.encoder.layers.0.mlp.fc2.weight', 'text_model.encoder.layers.1.layer_norm1.bias', 'text_model.encoder.layers.4.mlp.fc2.bias', 'text_model.encoder.layers.9.self_attn.v_proj.bias', 'text_model.encoder.layers.6.self_attn.out_proj.weight', 'text_model.encoder.layers.2.self_attn.q_proj.weight', 'text_model.encoder.layers.0.self_attn.out_proj.weight', 'text_model.encoder.layers.6.mlp.fc2.weight', 'text_model.encoder.layers.6.mlp.fc1.bias', 'text_model.encoder.layers.8.self_attn.v_proj.bias', 'text_model.encoder.layers.10.self_attn.out_proj.weight', 'text_model.encoder.layers.6.layer_norm1.weight', 'text_model.encoder.layers.2.self_attn.q_proj.bias', 'text_model.encoder.layers.2.mlp.fc2.bias', 'text_model.encoder.layers.8.mlp.fc2.bias', 'text_model.encoder.layers.1.self_attn.k_proj.weight']
- This IS expected if you are initializing CLIPVisionModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).
- This IS NOT expected if you are initializing CLIPVisionModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).
/admin/home/suraj/code/muse-experiments/ctrlnet/train_t2i_adapter.py:1331: DeprecationWarning: The 'warn' method is deprecated, use 'warning' instead
  logger.warn(
09/05/2023 22:46:22 - WARNING - __main__ - xFormers 0.0.16 cannot be used for training in some GPUs. If you observe problems during training, please update xFormers to at least 0.0.17. See https://huggingface.co/docs/diffusers/main/en/optimization/xformers for more details.
wandb: Currently logged in as: psuraj. Use `wandb login --relogin` to force relogin
wandb: wandb version 0.15.9 is available!  To upgrade, please run:
wandb:  $ pip install wandb --upgrade
wandb: Tracking run with wandb version 0.12.21
wandb: Run data is saved locally in /admin/home/suraj/code/muse-experiments/ctrlnet/wandb/run-20230905_224634-25abmfuh
wandb: Run `wandb offline` to turn off syncing.
wandb: Syncing run worthy-wave-64
wandb: ⭐️ View project at https://wandb.ai/psuraj/sd_xl_train_t2iadapter
wandb: 🚀 View run at https://wandb.ai/psuraj/sd_xl_train_t2iadapter/runs/25abmfuh
09/05/2023 22:46:38 - INFO - __main__ - ***** Running training *****
09/05/2023 22:46:38 - INFO - __main__ -   Num batches each epoch = 187504
09/05/2023 22:46:38 - INFO - __main__ -   Num Epochs = 1
09/05/2023 22:46:38 - INFO - __main__ -   Instantaneous batch size per device = 16
09/05/2023 22:46:38 - INFO - __main__ -   Total train batch size (w. parallel, distributed & accumulation) = 16
09/05/2023 22:46:38 - INFO - __main__ -   Gradient Accumulation steps = 1
09/05/2023 22:46:38 - INFO - __main__ -   Total optimization steps = 10
Checkpoint 'latest' does not exist. Starting a new training run.

Steps:   0% 0/10 [00:00<?, ?it/s]
Steps:  10% 1/10 [00:12<01:54, 12.70s/it]
Steps:  10% 1/10 [00:12<01:54, 12.70s/it, loss=0.041, lr=1e-5]09/05/2023 22:46:52 - INFO - torch.nn.parallel.distributed - Reducer buckets have been rebuilt in this iteration.

Steps:  20% 2/10 [00:16<01:01,  7.73s/it, loss=0.041, lr=1e-5]
Steps:  20% 2/10 [00:16<01:01,  7.73s/it, loss=0.0519, lr=1e-5]
Steps:  30% 3/10 [00:21<00:43,  6.14s/it, loss=0.0519, lr=1e-5]
Steps:  30% 3/10 [00:21<00:43,  6.14s/it, loss=0.0302, lr=1e-5]
Steps:  40% 4/10 [00:25<00:32,  5.40s/it, loss=0.0302, lr=1e-5]
Steps:  40% 4/10 [00:25<00:32,  5.40s/it, loss=0.0355, lr=1e-5]
Steps:  50% 5/10 [00:29<00:24,  4.98s/it, loss=0.0355, lr=1e-5]
Steps:  50% 5/10 [00:29<00:24,  4.98s/it, loss=0.0418, lr=1e-5]
Steps:  60% 6/10 [00:33<00:18,  4.73s/it, loss=0.0418, lr=1e-5]
Steps:  60% 6/10 [00:33<00:18,  4.73s/it, loss=0.033, lr=1e-5] 
Steps:  70% 7/10 [00:38<00:13,  4.58s/it, loss=0.033, lr=1e-5]
Steps:  70% 7/10 [00:38<00:13,  4.58s/it, loss=0.0901, lr=1e-5]
Steps:  80% 8/10 [00:42<00:08,  4.47s/it, loss=0.0901, lr=1e-5]
Steps:  80% 8/10 [00:42<00:08,  4.47s/it, loss=0.0388, lr=1e-5]
Steps:  90% 9/10 [00:46<00:04,  4.40s/it, loss=0.0388, lr=1e-5]
Steps:  90% 9/10 [00:46<00:04,  4.40s/it, loss=0.0824, lr=1e-5]
Steps: 100% 10/10 [00:50<00:00,  4.35s/it, loss=0.0824, lr=1e-5]09/05/2023 22:47:29 - INFO - __main__ - Running validation... 


Loading pipeline components...:   0% 0/7 [00:00<?, ?it/s]Loaded scheduler as EulerDiscreteScheduler from `scheduler` subfolder of stabilityai/stable-diffusion-xl-base-1.0.
Loaded tokenizer as CLIPTokenizer from `tokenizer` subfolder of stabilityai/stable-diffusion-xl-base-1.0.
Loaded tokenizer_2 as CLIPTokenizer from `tokenizer_2` subfolder of stabilityai/stable-diffusion-xl-base-1.0.


Loading pipeline components...:  71% 5/7 [00:00<00:00, 37.36it/s]Loaded text_encoder_2 as CLIPTextModelWithProjection from `text_encoder_2` subfolder of stabilityai/stable-diffusion-xl-base-1.0.
Loaded text_encoder as CLIPTextModel from `text_encoder` subfolder of stabilityai/stable-diffusion-xl-base-1.0.

Loading pipeline components...: 100% 7/7 [00:03<00:00,  2.31it/s]

Steps: 100% 10/10 [01:56<00:00,  4.35s/it, loss=0.0269, lr=1e-5]

image_control.png:   0% 0.00/1.30M [00:00<?, ?B/s]




Upload 6 LFS files:   0% 0/6 [00:00<?, ?it/s]



images_2.png:   0% 0.00/7.46M [00:00<?, ?B/s]


images_0.png:   0% 0.00/9.02M [00:00<?, ?B/s]





images_1.png:   0% 0.00/9.37M [00:00<?, ?B/s]






images_3.png:   0% 0.00/9.25M [00:00<?, ?B/s]

image_control.png:   1% 8.19k/1.30M [00:00<00:32, 40.3kB/s]






images_3.png:   0% 8.19k/9.25M [00:00<04:05, 37.6kB/s]


images_0.png:   0% 8.19k/9.02M [00:00<04:19, 34.7kB/s]





images_1.png:   0% 8.19k/9.37M [00:00<04:31, 34.4kB/s]



images_2.png:   0% 8.19k/7.46M [00:00<03:39, 33.9kB/s]

image_control.png:  14% 180k/1.30M [00:00<00:01, 672kB/s]  






images_3.png:   2% 180k/9.25M [00:00<00:14, 630kB/s]  


images_0.png:   2% 180k/9.02M [00:00<00:14, 621kB/s]  





images_1.png:   2% 180k/9.37M [00:00<00:14, 616kB/s]  



images_2.png:   2% 180k/7.46M [00:00<00:12, 603kB/s]  

image_control.png:  38% 500k/1.30M [00:00<00:00, 1.45MB/s]



images_2.png:   6% 475k/7.46M [00:00<00:05, 1.34MB/s]






images_3.png:   6% 541k/9.25M [00:00<00:05, 1.49MB/s]


images_0.png:   6% 557k/9.02M [00:00<00:05, 1.56MB/s]





images_1.png:   6% 582k/9.37M [00:00<00:05, 1.63MB/s]



images_2.png:  24% 1.79M/7.46M [00:00<00:01, 4.69MB/s]


images_0.png:  20% 1.78M/9.02M [00:00<00:01, 4.56MB/s]





images_1.png:  25% 2.32M/9.37M [00:00<00:01, 6.05MB/s]






images_3.png:  25% 2.34M/9.25M [00:00<00:01, 5.99MB/s]


images_0.png:  65% 5.89M/9.02M [00:00<00:00, 14.3MB/s]





images_1.png:  62% 5.85M/9.37M [00:00<00:00, 13.5MB/s]






images_3.png:  62% 5.74M/9.25M [00:00<00:00, 12.8MB/s]



images_2.png:  76% 5.64M/7.46M [00:00<00:00, 12.8MB/s]
image_control.png: 100% 1.30M/1.30M [00:00<00:00, 1.32MB/s]





Upload 6 LFS files:  17% 1/6 [00:00<00:04,  1.01it/s]

pytorch_model.bin:   0% 0.00/160M [00:00<?, ?B/s]

pytorch_model.bin:   0% 8.19k/160M [00:00<1:04:53, 41.0kB/s]
images_2.png: 100% 7.46M/7.46M [00:01<00:00, 6.20MB/s]

images_0.png: 100% 9.02M/9.02M [00:01<00:00, 7.38MB/s]





Upload 6 LFS files:  33% 2/6 [00:01<00:02,  1.83it/s]
images_1.png: 100% 9.37M/9.37M [00:01<00:00, 7.56MB/s]


pytorch_model.bin:   0% 180k/160M [00:00<03:55, 678kB/s]    
images_3.png: 100% 9.25M/9.25M [00:01<00:00, 6.94MB/s]





Upload 6 LFS files:  83% 5/6 [00:01<00:00,  5.49it/s]

pytorch_model.bin:   0% 516k/160M [00:00<01:45, 1.51MB/s]

pytorch_model.bin:   1% 2.26M/160M [00:00<00:25, 6.15MB/s]

pytorch_model.bin:   4% 5.79M/160M [00:00<00:11, 13.8MB/s]

pytorch_model.bin:   7% 10.4M/160M [00:00<00:06, 21.7MB/s]

pytorch_model.bin:  10% 15.9M/160M [00:00<00:04, 29.1MB/s]

pytorch_model.bin:  12% 18.9M/160M [00:01<00:12, 10.9MB/s]

pytorch_model.bin:  13% 21.1M/160M [00:01<00:11, 11.9MB/s]

pytorch_model.bin:  17% 26.7M/160M [00:01<00:07, 17.7MB/s]

pytorch_model.bin:  20% 31.6M/160M [00:02<00:05, 22.8MB/s]

pytorch_model.bin:  22% 34.9M/160M [00:02<00:11, 11.2MB/s]

pytorch_model.bin:  24% 38.9M/160M [00:02<00:08, 14.0MB/s]

pytorch_model.bin:  28% 44.4M/160M [00:02<00:06, 18.9MB/s]

pytorch_model.bin:  30% 48.0M/160M [00:03<00:07, 14.1MB/s]

pytorch_model.bin:  32% 50.5M/160M [00:03<00:09, 11.4MB/s]

pytorch_model.bin:  34% 53.8M/160M [00:03<00:07, 13.5MB/s]

pytorch_model.bin:  37% 58.6M/160M [00:04<00:05, 17.6MB/s]

pytorch_model.bin:  39% 62.7M/160M [00:04<00:04, 21.4MB/s]

pytorch_model.bin:  41% 65.8M/160M [00:04<00:07, 11.9MB/s]

pytorch_model.bin:  43% 68.8M/160M [00:04<00:07, 12.8MB/s]

pytorch_model.bin:  47% 74.4M/160M [00:05<00:04, 18.1MB/s]

pytorch_model.bin:  50% 79.1M/160M [00:05<00:03, 22.5MB/s]

pytorch_model.bin:  52% 82.4M/160M [00:05<00:07, 10.9MB/s]

pytorch_model.bin:  54% 85.9M/160M [00:06<00:05, 13.1MB/s]

pytorch_model.bin:  57% 90.8M/160M [00:06<00:04, 17.0MB/s]

pytorch_model.bin:  60% 95.6M/160M [00:06<00:03, 20.9MB/s]

pytorch_model.bin:  62% 98.9M/160M [00:07<00:05, 11.1MB/s]

pytorch_model.bin:  64% 102M/160M [00:07<00:04, 12.7MB/s] 

pytorch_model.bin:  67% 107M/160M [00:07<00:03, 16.6MB/s]

pytorch_model.bin:  69% 111M/160M [00:07<00:02, 18.4MB/s]

pytorch_model.bin:  71% 113M/160M [00:08<00:04, 10.5MB/s]

pytorch_model.bin:  72% 115M/160M [00:08<00:03, 11.3MB/s]

pytorch_model.bin:  75% 120M/160M [00:08<00:02, 14.7MB/s]

pytorch_model.bin:  78% 125M/160M [00:08<00:01, 19.5MB/s]

pytorch_model.bin:  80% 128M/160M [00:08<00:02, 14.0MB/s]

pytorch_model.bin:  82% 130M/160M [00:09<00:02, 11.1MB/s]

pytorch_model.bin:  83% 133M/160M [00:09<00:02, 12.0MB/s]

pytorch_model.bin:  86% 138M/160M [00:09<00:01, 17.0MB/s]

pytorch_model.bin:  90% 144M/160M [00:09<00:00, 22.6MB/s]

pytorch_model.bin:  92% 147M/160M [00:10<00:01, 11.8MB/s]

pytorch_model.bin:  94% 150M/160M [00:10<00:00, 13.8MB/s]

pytorch_model.bin:  97% 155M/160M [00:10<00:00, 17.8MB/s]

pytorch_model.bin:  99% 159M/160M [00:10<00:00, 20.7MB/s]
pytorch_model.bin: 100% 160M/160M [00:11<00:00, 14.3MB/s]

Upload 6 LFS files: 100% 6/6 [00:12<00:00,  2.02s/it]