PrunaAI

/

MILVLG-imp-v1-3b-QUANTO-float8bit-smashed

like 0

Follow

Pruna AI 171

• "torch.device",
• "transformers_modules.MILVLG.imp-v1-3b.634c7fcac78f045a4f8359c70589ffc55bf2de84.configuration_imp.ImpConfig",
• "torch._utils._rebuild_parameter",
• "torch.float8_e4m3fn",
• "torch.float16",
• "transformers_modules.MILVLG.imp-v1-3b.634c7fcac78f045a4f8359c70589ffc55bf2de84.modeling_imp.PhiMLP",
• "transformers.activations.NewGELUActivation",
• "collections.OrderedDict",
• "torch.nn.modules.container.Sequential",
• "transformers_modules.MILVLG.imp-v1-3b.634c7fcac78f045a4f8359c70589ffc55bf2de84.vision_encoder.simple_image_processor",
• "transformers_modules.MILVLG.imp-v1-3b.634c7fcac78f045a4f8359c70589ffc55bf2de84.vision_encoder.SiglipEncoderLayer",
• "transformers.generation.configuration_utils.GenerationConfig",
• "torch.HalfStorage",
• "transformers_modules.MILVLG.imp-v1-3b.634c7fcac78f045a4f8359c70589ffc55bf2de84.vision_encoder.VisionTower",
• "transformers_modules.MILVLG.imp-v1-3b.634c7fcac78f045a4f8359c70589ffc55bf2de84.configuration_imp.SiglipVisionConfig",
• "torch._utils._rebuild_tensor_v2",
• "torch.FloatStorage",
• "transformers_modules.MILVLG.imp-v1-3b.634c7fcac78f045a4f8359c70589ffc55bf2de84.vision_encoder.SiglipAttention",
• "torch.nn.modules.sparse.Embedding",
• "transformers_modules.MILVLG.imp-v1-3b.634c7fcac78f045a4f8359c70589ffc55bf2de84.modeling_imp.ImpModel",
• "torch.nn.modules.dropout.Dropout",
• "torch.nn.modules.linear.Identity",
• "transformers_modules.MILVLG.imp-v1-3b.634c7fcac78f045a4f8359c70589ffc55bf2de84.modeling_imp.ImpForCausalLM",
• "quanto.tensor.qtype.qtype",
• "torch.nn.modules.normalization.LayerNorm",
• "transformers_modules.MILVLG.imp-v1-3b.634c7fcac78f045a4f8359c70589ffc55bf2de84.vision_encoder.SiglipVisionModel",
• "transformers_modules.MILVLG.imp-v1-3b.634c7fcac78f045a4f8359c70589ffc55bf2de84.modeling_imp.PhiDecoderLayer",
• "quanto.nn.qlinear.QLinear",
• "transformers_modules.MILVLG.imp-v1-3b.634c7fcac78f045a4f8359c70589ffc55bf2de84.modeling_imp.PhiAttention",
• "transformers_modules.MILVLG.imp-v1-3b.634c7fcac78f045a4f8359c70589ffc55bf2de84.vision_encoder.SiglipEncoder",
• "__builtin__.set",
• "transformers_modules.MILVLG.imp-v1-3b.634c7fcac78f045a4f8359c70589ffc55bf2de84.modeling_imp.PhiRotaryEmbedding",
• "quanto.nn.qconv2d.QConv2d",
• "torch.nn.modules.activation.GELU",
• "transformers_modules.MILVLG.imp-v1-3b.634c7fcac78f045a4f8359c70589ffc55bf2de84.vision_encoder.SiglipVisionTransformer",
• "transformers_modules.MILVLG.imp-v1-3b.634c7fcac78f045a4f8359c70589ffc55bf2de84.vision_encoder.SiglipVisionEmbeddings",
• "torch.nn.modules.container.ModuleList",
• "torch.LongStorage",
• "transformers_modules.MILVLG.imp-v1-3b.634c7fcac78f045a4f8359c70589ffc55bf2de84.vision_encoder.SiglipMLP",
• "transformers.activations.PytorchGELUTanh"

How to fix it?