Text Generation
PEFT
Safetensors
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Update README.md

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@@ -19,7 +19,7 @@ Falcon-7b-openassistant-peft is a chatbot-like model for dialogue generation. It
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  ## Model Details
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- The model was fine-tuned in 8-bit precision using 🤗 `peft` adapters, `transformers`, and `bitsandbytes`. Training relied on a method called "Low Rank Adapters" ([LoRA](https://arxiv.org/pdf/2106.09685.pdf)), specifically the [QLoRA](https://arxiv.org/abs/2305.14314) variant. The run took approximately 6.25 hours and was executed on a workstation with a single A100-SXM NVIDIA GPU with 37 GB of available memory. See attached [Colab Notebook](https://huggingface.co/dfurman/falcon-7b-chat-oasst1/blob/main/finetune_falcon7b_oasst1_with_bnb_peft.ipynb) for the code and hyperparams used to train the model.
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  ### Model Date
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@@ -117,7 +117,7 @@ from peft import PeftModel, PeftConfig
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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  # load the model
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- peft_model_id = "dfurman/falcon-7b-chat-oasst1"
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  config = PeftConfig.from_pretrained(peft_model_id)
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  model = AutoModelForCausalLM.from_pretrained(
@@ -170,7 +170,7 @@ print(generated_text.split("<human>: ")[1].split("<bot>: ")[-1])
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  ## Reproducibility
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- See attached [Colab Notebook](https://huggingface.co/dfurman/falcon-7b-chat-oasst1/blob/main/finetune_falcon7b_oasst1_with_bnb_peft.ipynb) for the code (and hyperparams) used to train the model.
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  ### CUDA Info
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  ## Model Details
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+ The model was fine-tuned in 8-bit precision using 🤗 `peft` adapters, `transformers`, and `bitsandbytes`. Training relied on a method called "Low Rank Adapters" ([LoRA](https://arxiv.org/pdf/2106.09685.pdf)), specifically the [QLoRA](https://arxiv.org/abs/2305.14314) variant. The run took approximately 6.25 hours and was executed on a workstation with a single A100-SXM NVIDIA GPU with 37 GB of available memory. See attached [Colab Notebook](https://huggingface.co/dfurman/falcon-7b-openassistant-peft/blob/main/finetune_falcon7b_oasst1_with_bnb_peft.ipynb) for the code and hyperparams used to train the model.
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  ### Model Date
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  from transformers import AutoModelForCausalLM, AutoTokenizer
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  # load the model
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+ peft_model_id = "dfurman/falcon-7b-openassistant-peft"
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  config = PeftConfig.from_pretrained(peft_model_id)
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  model = AutoModelForCausalLM.from_pretrained(
 
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  ## Reproducibility
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+ See attached [Colab Notebook](https://huggingface.co/dfurman/falcon-7b-openassistant-peft/blob/main/finetune_falcon7b_oasst1_with_bnb_peft.ipynb) for the code (and hyperparams) used to train the model.
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  ### CUDA Info
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