Upload GPTRefactForCausalLM (#5)
Browse files- Upload GPTRefactForCausalLM (a4ba9934cfef545c1a36eed0f94b50b431bbd746)
- configuration_gpt_refact.py +1 -1
- modeling_gpt_refact.py +3 -2
- pytorch_model.bin +1 -1
configuration_gpt_refact.py
CHANGED
@@ -32,7 +32,7 @@ class GPTRefactConfig(PretrainedConfig):
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use_cache=True,
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bos_token_id=-1,
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eos_token_id=0,
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max_position_embeddings: int =
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multi_query: bool = True,
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attention_softmax_in_fp32=False,
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scale_attention_softmax_in_fp32=False,
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use_cache=True,
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bos_token_id=-1,
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eos_token_id=0,
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max_position_embeddings: int = 4096,
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multi_query: bool = True,
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attention_softmax_in_fp32=False,
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scale_attention_softmax_in_fp32=False,
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modeling_gpt_refact.py
CHANGED
@@ -346,9 +346,10 @@ class GPTRefactModel(GPTRefactPreTrainedModel):
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self.h = nn.ModuleList([GPTRefactBlock(config, layer_idx=i) for i in range(config.num_hidden_layers)])
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max_positions = config.max_position_embeddings
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self.register_buffer(
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"bias", torch.tril(torch.ones((max_positions, max_positions), dtype=torch.bool)),
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)
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self.gradient_checkpointing = False
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self.h = nn.ModuleList([GPTRefactBlock(config, layer_idx=i) for i in range(config.num_hidden_layers)])
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self.max_positions = config.max_position_embeddings
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self.register_buffer(
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"bias", torch.tril(torch.ones((self.max_positions, self.max_positions), dtype=torch.bool)),
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persistent=False
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)
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self.gradient_checkpointing = False
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pytorch_model.bin
CHANGED
@@ -1,3 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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-
oid sha256:
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size 6343461637
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:81388e4a168bb437a7a09af6c8b6c2943990276ee62c2f449cd2bdff257e8860
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size 6343461637
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