flow-poke-transformer

3
license:cc-by-nc-4.0
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CompVis
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Quick Summary

[](https://compvis.github.io/flow-poke-transformer/) [](https://huggingface.co/papers/2510.12777) [](https://github.com/CompVis/flow-poke-transformer) [](https:...

Code Examples

pythonpytorch
import torch

model = torch.hub.load("CompVis/flow_poke_transformer", "fpt_base")
pythonpytorch
import torch

model = torch.hub.load("CompVis/flow_poke_transformer", "fpt_base")
pythonpytorch
import torch

model = torch.hub.load("CompVis/flow_poke_transformer", "fpt_base")
pythonpytorch
import torch

model = torch.hub.load("CompVis/flow_poke_transformer", "fpt_base")
pythonpytorch
import torch

model = torch.hub.load("CompVis/flow_poke_transformer", "fpt_base")
pythonpytorch
import torch

model = torch.hub.load("CompVis/flow_poke_transformer", "fpt_base")
pythonpytorch
import torch

model = torch.hub.load("CompVis/flow_poke_transformer", "fpt_base")
pythonpytorch
import torch

model = torch.hub.load("CompVis/flow_poke_transformer", "fpt_base")
pythonpytorch
import torch

model = torch.hub.load("CompVis/flow_poke_transformer", "fpt_base")
pythonpytorch
import torch

model = torch.hub.load("CompVis/flow_poke_transformer", "fpt_base")
pythonpytorch
import torch

model = torch.hub.load("CompVis/flow_poke_transformer", "fpt_base")
pythonpytorch
import torch

model = torch.hub.load("CompVis/flow_poke_transformer", "fpt_base")
pythonpytorch
import torch
from flow_poke.model import FlowPokeTransformer_Base

model: FlowPokeTransformer_Base = FlowPokeTransformer_Base()
state_dict = torch.load("fpt_base.pt") # You would need to download the weights separately
model.load_state_dict(state_dict)
model.requires_grad_(False)
model.eval()
pythonpytorch
import torch
from flow_poke.model import FlowPokeTransformer_Base

model: FlowPokeTransformer_Base = FlowPokeTransformer_Base()
state_dict = torch.load("fpt_base.pt") # You would need to download the weights separately
model.load_state_dict(state_dict)
model.requires_grad_(False)
model.eval()
pythonpytorch
import torch
from flow_poke.model import FlowPokeTransformer_Base

model: FlowPokeTransformer_Base = FlowPokeTransformer_Base()
state_dict = torch.load("fpt_base.pt") # You would need to download the weights separately
model.load_state_dict(state_dict)
model.requires_grad_(False)
model.eval()
pythonpytorch
import torch
from flow_poke.model import FlowPokeTransformer_Base

model: FlowPokeTransformer_Base = FlowPokeTransformer_Base()
state_dict = torch.load("fpt_base.pt") # You would need to download the weights separately
model.load_state_dict(state_dict)
model.requires_grad_(False)
model.eval()
pythonpytorch
import torch
from flow_poke.model import FlowPokeTransformer_Base

model: FlowPokeTransformer_Base = FlowPokeTransformer_Base()
state_dict = torch.load("fpt_base.pt") # You would need to download the weights separately
model.load_state_dict(state_dict)
model.requires_grad_(False)
model.eval()
pythonpytorch
import torch
from flow_poke.model import FlowPokeTransformer_Base

model: FlowPokeTransformer_Base = FlowPokeTransformer_Base()
state_dict = torch.load("fpt_base.pt") # You would need to download the weights separately
model.load_state_dict(state_dict)
model.requires_grad_(False)
model.eval()
pythonpytorch
import torch
from flow_poke.model import FlowPokeTransformer_Base

model: FlowPokeTransformer_Base = FlowPokeTransformer_Base()
state_dict = torch.load("fpt_base.pt") # You would need to download the weights separately
model.load_state_dict(state_dict)
model.requires_grad_(False)
model.eval()
pythonpytorch
import torch
from flow_poke.model import FlowPokeTransformer_Base

model: FlowPokeTransformer_Base = FlowPokeTransformer_Base()
state_dict = torch.load("fpt_base.pt") # You would need to download the weights separately
model.load_state_dict(state_dict)
model.requires_grad_(False)
model.eval()
pythonpytorch
import torch
from flow_poke.model import FlowPokeTransformer_Base

model: FlowPokeTransformer_Base = FlowPokeTransformer_Base()
state_dict = torch.load("fpt_base.pt") # You would need to download the weights separately
model.load_state_dict(state_dict)
model.requires_grad_(False)
model.eval()
pythonpytorch
import torch
from flow_poke.model import FlowPokeTransformer_Base

model: FlowPokeTransformer_Base = FlowPokeTransformer_Base()
state_dict = torch.load("fpt_base.pt") # You would need to download the weights separately
model.load_state_dict(state_dict)
model.requires_grad_(False)
model.eval()
pythonpytorch
import torch
from flow_poke.model import FlowPokeTransformer_Base

model: FlowPokeTransformer_Base = FlowPokeTransformer_Base()
state_dict = torch.load("fpt_base.pt") # You would need to download the weights separately
model.load_state_dict(state_dict)
model.requires_grad_(False)
model.eval()
pythonpytorch
import torch
from flow_poke.model import FlowPokeTransformer_Base

model: FlowPokeTransformer_Base = FlowPokeTransformer_Base()
state_dict = torch.load("fpt_base.pt") # You would need to download the weights separately
model.load_state_dict(state_dict)
model.requires_grad_(False)
model.eval()

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