Let’s walk through each of these steps in detail. Requirements and Setup# This tutorial needs to be run from inside a NeMo docker container. If you are not running this tutorial through a NeMo docker container, please refer to theRiva NMT Tutorialsto get started....
For this demo, we will download videos of NBA highlights and create a YOLO model that can accurately detect which players on the court are actively holding the ball. The challenge here is to get the model to accurately and reliably detect and discern the ball handler from the other players ...
pipe = StableDiffusionPipeline.from_pretrained(modelid, revision="fp16", torch_dtype=torch.float32, use_auth_token=auth_token) # Move the pipeline to the specified device (CPU) pipe.to(device) # Define the function to generate the image from the prompt def generate(): ...
Check 'element::Type::merge(inputs_et, inputs_et, get_input_element_type(i))' failed at src/core/src/op/concat.cpp:36: While validating node 'opset1::Concat Concat_6575 (opset6::GatherElements __module.model.23/aten::gather/GatherElements[0]:f32[?,?,?], opset1::Unsqueeze __mod...
🐛 Describe the bug This is trying to do a BE task to unblock #130977. The problem is very similar to #120261, though that one uses torch.export with strict=True. repro: import numpy as np import torch class MyNumpyModel(torch.nn.Module):...
The completion of this quest rewards you with a rune, allowing you to get mid-tier runes early in the game. On Normal Difficulty, you can get runes up to the Amn Rune. On Nightmare Difficulty, you can be rewarded with the Sol Rune all the way to the Um Rune. Finally, on Hell ...
Then, we can take a look at our training environment provided to us for free from Google Colab. importtorchfromIPython.displayimportImage# for displaying imagesfromutils.google_utilsimportgdrive_download# for downloading models/datasetsprint('torch %s %s'%(torch.__version__,torch.cuda.get_device...
action, logprob, _, value = agent.get_action_and_value(next_obs) values[step] = value.flatten() actions[step] = action logprobs[step] = logprob next_obs, reward, done, info = envs.step(action.cpu().numpy()) rewards[step] = torch.tensor(reward).to(device).view(-1)withtorch....
When editing photos in VSCO, you can easily compare the before and after images. Tap and hold the image to see the original unedited version. Release your finger to return to the edited photo. 2.2 Download More VSCO Filters Thefree VSCO appcomes with a basic set of 10 filters to get yo...
There are many other other online courses you can take after this one (see My answer to What is the best MOOC to get started in Machine Learning?)but at this point you are mostly ready to go to the next step. Implement an algorithm My recommended next step is the following. Get a ...