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Update README.md

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@@ -4,6 +4,8 @@ license: apache-2.0
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  language:
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  - en
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  pipeline_tag: conversational
 
 
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  ---
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  ## ChatLM
@@ -24,7 +26,7 @@ model_path = "ayoolaolafenwa/ChatLM"
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  tokenizer = AutoTokenizer.from_pretrained(model_path)
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  model = AutoModelForCausalLM.from_pretrained(model_path, trust_remote_code = True,
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- torch_dtype=torch.bfloat16)
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  prompt = "<user>: Give me a financial advise on investing in stocks. <chatbot>: "
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@@ -132,5 +134,4 @@ Check the the modified dataset https://huggingface.co/datasets/ayoolaolafenwa/sf
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  ChatLM was supervised finetuned with pretrained [Falcon 1-Billion parameters model](https://huggingface.co/tiiuae/falcon-rw-1b) trained on 350-Billion tokens
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  of RefinedWeb. It was trained with a single H100 GPU for 1 epoch. It achieves Perplexity *1.738*. Check the full code for supervised finetune
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- training on its github repository https://github.com/ayoolaolafenwa/ChatLM/tree/main
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-
 
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  language:
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  - en
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  pipeline_tag: conversational
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+ datasets:
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+ - ayoolaolafenwa/sft-data
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  ---
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  ## ChatLM
 
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  tokenizer = AutoTokenizer.from_pretrained(model_path)
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  model = AutoModelForCausalLM.from_pretrained(model_path, trust_remote_code = True,
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+ torch_dtype=torch.bfloat16).to("cuda")
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  prompt = "<user>: Give me a financial advise on investing in stocks. <chatbot>: "
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  ChatLM was supervised finetuned with pretrained [Falcon 1-Billion parameters model](https://huggingface.co/tiiuae/falcon-rw-1b) trained on 350-Billion tokens
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  of RefinedWeb. It was trained with a single H100 GPU for 1 epoch. It achieves Perplexity *1.738*. Check the full code for supervised finetune
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+ training on its github repository https://github.com/ayoolaolafenwa/ChatLM/tree/main