add model
Browse files- config.json +36 -0
- modeling_gpt2.py +32 -0
- pytorch_model.bin +3 -0
config.json
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{
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"_name_or_path": "/content/drive/MyDrive/ColabModels/GPT2SmallTheseus/pytorch_model/",
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"activation_function": "gelu_new",
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"architectures": [
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"GPT2LMHeadModel"
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],
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"attn_pdrop": 0.1,
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"auto_map": {
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"AutoModel": "modeling_gpt2.GPT2LMHeadModel"
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},
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"bos_token_id": 50256,
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"embd_pdrop": 0.1,
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"eos_token_id": 50256,
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"initializer_range": 0.02,
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"layer_norm_epsilon": 1e-05,
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"model_type": "gpt2",
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"n_ctx": 1024,
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"n_embd": 768,
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"n_head": 12,
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"n_inner": null,
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"n_layer": 6,
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"n_positions": 1024,
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"reorder_and_upcast_attn": false,
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"resid_pdrop": 0.1,
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"scale_attn_by_inverse_layer_idx": false,
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"scale_attn_weights": true,
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"summary_activation": null,
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"summary_first_dropout": 0.1,
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"summary_proj_to_labels": true,
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"summary_type": "cls_index",
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"summary_use_proj": true,
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"torch_dtype": "float32",
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"transformers_version": "4.18.0",
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"use_cache": true,
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"vocab_size": 50257
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}
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modeling_gpt2.py
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from torch import nn
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from transformers import GPT2LMHeadModel as GPT2LMHeadModelBase
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from transformers.models.gpt2.modeling_gpt2 import GPT2Block as GPT2BlockBase
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class GPT2Block(GPT2BlockBase):
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def forward(self, x, layer_past=None,
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attention_mask=None, head_mask=None, use_cache=False,
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encoder_hidden_states=None, encoder_attention_mask=None, output_attentions=None):
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x = self.ln_1(x)
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output_attn = self.attn(
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x, layer_past=layer_past,
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attention_mask=attention_mask,
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head_mask=head_mask,
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use_cache=use_cache)
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a = output_attn[0]
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x = x + a
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m = self.mlp(self.ln_2(x))
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x = x + m
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outputs = (x,) + output_attn[1:]
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return outputs
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class GPT2LMHeadModel(GPT2LMHeadModelBase):
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def __init__(self, config):
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super().__init__(config)
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self.transformer.h = nn.ModuleList([GPT2Block(config, layer_idx) for layer_idx in range(config.n_layer)])
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:e20db5c11921f7238bb88123f2b19d9dd13b7b67d7c1345ace9f30876823ed93
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size 333967901
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