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PrunaAI
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ucsahin-TraVisionLM-base-QUANTO-int2bit-smashed
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ucsahin-TraVisionLM-base-QUANTO-int2bit-smashed
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added_tokens.json
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model.pt
pickle
Detected Pickle imports (42)
"transformers.models.siglip.modeling_siglip.SiglipVisionModel"
,
"torch.FloatStorage"
,
"transformers.generation.configuration_utils.GenerationConfig"
,
"transformers_modules.ucsahin.TraVisionLM-base.6809b320caef3ad10c67a9f182cdbea59ef4c257.configuration_travisionlm.TraVisionLMConfig"
,
"torch._utils._rebuild_parameter"
,
"transformers.models.gpt2.modeling_gpt2.GPT2Block"
,
"torch.float32"
,
"transformers_modules.ucsahin.TraVisionLM-base.6809b320caef3ad10c67a9f182cdbea59ef4c257.modeling_travisionlm.TraVisionMultiModalProjector"
,
"transformers_modules.ucsahin.TraVisionLM-base.6809b320caef3ad10c67a9f182cdbea59ef4c257.modeling_travisionlm.TraVisionForCausalLM"
,
"transformers.models.siglip.configuration_siglip.SiglipVisionConfig"
,
"transformers.models.siglip.modeling_siglip.SiglipEncoder"
,
"transformers.activations.NewGELUActivation"
,
"torch.nn.modules.dropout.Dropout"
,
"torch.nn.modules.container.ModuleList"
,
"torch.BoolStorage"
,
"transformers.models.siglip.modeling_siglip.SiglipVisionEmbeddings"
,
"collections.OrderedDict"
,
"transformers.models.gpt2.configuration_gpt2.GPT2Config"
,
"transformers.activations.PytorchGELUTanh"
,
"transformers.models.gpt2.modeling_gpt2.GPT2MLP"
,
"torch.nn.modules.activation.MultiheadAttention"
,
"torch.nn.modules.container.Sequential"
,
"torch.int8"
,
"torch.LongStorage"
,
"torch.nn.modules.activation.GELU"
,
"transformers.models.gpt2.modeling_gpt2.GPT2SdpaAttention"
,
"quanto.nn.qlinear.QLinear"
,
"transformers.models.siglip.modeling_siglip.SiglipVisionTransformer"
,
"quanto.nn.qconv2d.QConv2d"
,
"__builtin__.set"
,
"quanto.tensor.qtype.qtype"
,
"torch.nn.modules.normalization.LayerNorm"
,
"transformers.models.siglip.modeling_siglip.SiglipMultiheadAttentionPoolingHead"
,
"transformers.models.siglip.modeling_siglip.SiglipEncoderLayer"
,
"torch._utils._rebuild_tensor_v2"
,
"transformers.models.siglip.modeling_siglip.SiglipAttention"
,
"transformers.models.siglip.modeling_siglip.SiglipMLP"
,
"transformers.models.gpt2.modeling_gpt2.GPT2Model"
,
"transformers.pytorch_utils.Conv1D"
,
"torch.nn.modules.sparse.Embedding"
,
"torch.device"
,
"transformers.models.gpt2.modeling_gpt2.GPT2LMHeadModel"
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tokenizer.json
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