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README.md
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@@ -97,7 +97,7 @@ import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("Bochkov/emergent-semantics-model-1024-float-335m")
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model = AutoModelForCausalLM.from_pretrained("Bochkov/emergent-semantics-model-1024-float-335m", trust_remote_code=True)
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inputs = torch.tensor([tokenizer.encode("Question: What is the capital of Japan?\nAnswer:")], dtype=torch.long, device='cuda')
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@@ -108,6 +108,9 @@ outputs = model.generate(
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print(tokenizer.decode(outputs[0].tolist()))
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```
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---
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("Bochkov/emergent-semantics-model-1024-float-335m")
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model = AutoModelForCausalLM.from_pretrained("Bochkov/emergent-semantics-model-1024-float-335m", trust_remote_code=True).to('cuda')
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inputs = torch.tensor([tokenizer.encode("Question: What is the capital of Japan?\nAnswer:")], dtype=torch.long, device='cuda')
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)
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print(tokenizer.decode(outputs[0].tolist()))
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#Question: What is the capital of Japan?
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#Answer:Tokyo Metropolitan
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```
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