xinchen9
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Llama3.1_CoT_V1

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xinchen9 commited on 13 days ago

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1 Parent(s): c5ed4b8

[Update]Update model name

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README.md +2 -2

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@@ -6,7 +6,7 @@ license: apache-2.0
 Introducing xinchen9/llama3-b8-ft, an advanced language model comprising 8 billion parameters. It has been fine-trained based on
 [meta-llama/Meta-Llama-3.1-8B](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B).
-The llama3-b8 model was fine-tuning on dataset [CoT_ollection](https://huggingface.co/datasets/kaist-ai/CoT-Collection).
 The training step is 30,000. The batch of each device is 8 and toal GPU is 5.
@@ -17,7 +17,7 @@ Here give some examples of how to use our model.
 import torch
 from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig
-model_name = "xinchen9/Llama3.1_CoT"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
 model.generation_config = GenerationConfig.from_pretrained(model_name)

 Introducing xinchen9/llama3-b8-ft, an advanced language model comprising 8 billion parameters. It has been fine-trained based on
 [meta-llama/Meta-Llama-3.1-8B](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B).
+The llama3-b8 model was fine-tuning on dataset [CoT_Collection](https://huggingface.co/datasets/kaist-ai/CoT-Collection).
 The training step is 30,000. The batch of each device is 8 and toal GPU is 5.
 import torch
 from transformers import AutoTokenizer, AutoModelForCausalLM, GenerationConfig
+model_name = "xinchen9/Llama3.1_CoT_V1"
 tokenizer = AutoTokenizer.from_pretrained(model_name)
 model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.bfloat16, device_map="auto")
 model.generation_config = GenerationConfig.from_pretrained(model_name)