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Upgrade transformers version to 4.36.0 (#2046)
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@ -10,7 +10,7 @@ numpy
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tokenizers>=0.15.0
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huggingface_hub<0.18,>=0.16.4
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einops # Required for phi-1_5
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transformers >= 4.34.0 # Required for Mistral.
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transformers >= 4.36.0 # Required for Mixtral.
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fastapi
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uvicorn[standard]
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pydantic == 1.10.13 # Required for OpenAI server.
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@ -7,7 +7,7 @@ sentencepiece # Required for LLaMA tokenizer.
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numpy
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einops # Required for phi-1_5
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torch >= 2.1.1
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transformers >= 4.34.0 # Required for Mistral.
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transformers >= 4.36.0 # Required for Mixtral.
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xformers >= 0.0.23 # Required for CUDA 12.1.
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fastapi
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uvicorn[standard]
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@ -29,7 +29,7 @@ import torch
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import torch.nn.functional as F
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from torch import nn
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from transformers import MistralConfig
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from transformers import MixtralConfig
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try:
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import megablocks.ops as ops
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@ -395,7 +395,7 @@ class MixtralDecoderLayer(nn.Module):
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def __init__(
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self,
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config: MistralConfig,
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config: MixtralConfig,
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) -> None:
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super().__init__()
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self.hidden_size = config.hidden_size
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@ -443,7 +443,7 @@ class MixtralForCausalLM(nn.Module):
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def __init__(
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self,
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config: MistralConfig,
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config: MixtralConfig,
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linear_method: Optional[LinearMethodBase] = None,
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) -> None:
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super().__init__()
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