GPT Neo few fixes (#10968)
* fix checkpoint names * auto model * fix doc
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@@ -432,7 +432,7 @@ class GPTNeoModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestCase
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@slow
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def test_batch_generation(self):
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model = GPTNeoForCausalLM.from_pretrained("EleutherAI/gpt_neo_xl")
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model = GPTNeoForCausalLM.from_pretrained("EleutherAI/gpt-neo-1.3B")
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model.to(torch_device)
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tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
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@@ -486,7 +486,7 @@ class GPTNeoModelLanguageGenerationTest(unittest.TestCase):
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@slow
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def test_lm_generate_gpt_neo(self):
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for checkpointing in [True, False]:
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model = GPTNeoForCausalLM.from_pretrained("EleutherAI/gpt_neo_xl", gradient_checkpointing=checkpointing)
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model = GPTNeoForCausalLM.from_pretrained("EleutherAI/gpt-neo-1.3B", gradient_checkpointing=checkpointing)
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model.to(torch_device)
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input_ids = torch.tensor([[464, 3290]], dtype=torch.long, device=torch_device) # The dog
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# fmt: off
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@@ -497,8 +497,8 @@ class GPTNeoModelLanguageGenerationTest(unittest.TestCase):
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@slow
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def test_gpt_neo_sample(self):
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tokenizer = GPT2Tokenizer.from_pretrained("EleutherAI/gpt_neo_xl")
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model = GPTNeoForCausalLM.from_pretrained("EleutherAI/gpt_neo_xl")
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tokenizer = GPT2Tokenizer.from_pretrained("EleutherAI/gpt-neo-1.3B")
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model = GPTNeoForCausalLM.from_pretrained("EleutherAI/gpt-neo-1.3B")
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model.to(torch_device)
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torch.manual_seed(0)
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