Update transformers version in installation instructions
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README.md
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@@ -85,7 +85,7 @@ To import from HuggingFace, you will need to install these versions:
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```bash
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uv pip install datasets==3.2.0 #for HF datasets
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uv pip install transformers==4.51.
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uv pip install huggingface_hub~=0.34.4
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```
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@@ -100,8 +100,8 @@ from transformers import AutoModelForCausalLM, AutoTokenizer, set_seed
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set_seed(0)
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torch.set_default_device("cuda")
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model = AutoModelForCausalLM.from_pretrained("microsoft/Dayhoff-
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tokenizer = AutoTokenizer.from_pretrained("microsoft/Dayhoff-
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inputs = tokenizer(tokenizer.bos_token, return_tensors="pt", return_token_type_ids=False)
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@@ -263,4 +263,4 @@ The code and datasets released in this repository are provided for research and
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If you use the code, data, models, or results. please cite our [preprint](https://aka.ms/dayhoff/preprint).
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## Data Summary
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https://huggingface.co/microsoft/Dayhoff-
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```bash
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uv pip install datasets==3.2.0 #for HF datasets
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uv pip install transformers==4.51.3
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uv pip install huggingface_hub~=0.34.4
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```
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set_seed(0)
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torch.set_default_device("cuda")
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model = AutoModelForCausalLM.from_pretrained("microsoft/Dayhoff-170m-GR").to("cuda")
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tokenizer = AutoTokenizer.from_pretrained("microsoft/Dayhoff-170m-GR", trust_remote_code=True)
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inputs = tokenizer(tokenizer.bos_token, return_tensors="pt", return_token_type_ids=False)
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If you use the code, data, models, or results. please cite our [preprint](https://aka.ms/dayhoff/preprint).
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## Data Summary
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https://huggingface.co/microsoft/Dayhoff-170m-GR/blob/main/data_summary_card.md
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