Closed work4cs closed 1 month ago
We can give An Example in READ.ME for using other openclip style checkpoints:
from bioclip import CustomLabelsClassifier classifier = CustomLabelsClassifier(['Schistocerca americana', 'Schistocerca lineata'], device='cuda', model_str='hf-hub:laion/CLIP-ViT-B-16-laion2B-s34B-b88K') predictions = classifier.predict("image.png")
Also could even allow openai checkpoint or local checkpoint by passing pretrained parameters.
class BaseClassifier(object): def __init__(self, device: Union[str, torch.device] = 'cpu', model_str: str = MODEL_STR, pretrained: str = 'openai'): self.model = create_bioclip_model(device=device, model_str=model_str, pretrained: str =pretrained )
def create_bioclip_model(model_str, device="cuda", pretrained: str = 'openai'): model = create_model(model_str, output_dict=True, require_pretrained=True, pretrained: str=pretrained)
We can give An Example in READ.ME for using other openclip style checkpoints:
Also could even allow openai checkpoint or local checkpoint by passing pretrained parameters.
class BaseClassifier(object): def __init__(self, device: Union[str, torch.device] = 'cpu', model_str: str = MODEL_STR, pretrained: str = 'openai'): self.model = create_bioclip_model(device=device, model_str=model_str, pretrained: str =pretrained )def create_bioclip_model(model_str, device="cuda", pretrained: str = 'openai'): model = create_model(model_str, output_dict=True, require_pretrained=True, pretrained: str=pretrained)