Update README.md

README.md

@@ -8,9 +8,15 @@ base_model: tiiuae/falcon-7b
 inference: false
 ---
 
-# falcon-7b-openassistant-peft 🦅
+# Falcon-7B-Chat-v0.1 🦅
 
-Falcon-7b-openassistant-peft is a chatbot model for dialogue generation. It was built by fine-tuning [Falcon-7B](https://huggingface.co/tiiuae/falcon-7b) on the [OpenAssistant/oasst1](https://huggingface.co/datasets/OpenAssistant/oasst1) dataset. This repo only includes the LoRA adapters from fine-tuning with 🤗's [peft](https://github.com/huggingface/peft) package. 
+<div align="left">
+
+<img src="./falcon.webp" width="150px">
+
+</div>
+
+Falcon-7B-Chat-v0.1 is a chatbot model for dialogue generation. It was built by fine-tuning [Falcon-7B](https://huggingface.co/tiiuae/falcon-7b) on the [OpenAssistant/oasst1](https://huggingface.co/datasets/OpenAssistant/oasst1) dataset. This repo only includes the LoRA adapters from fine-tuning with 🤗's [peft](https://github.com/huggingface/peft) package. 
 
 ## Model Summary
 
@@ -22,7 +28,7 @@ Falcon-7b-openassistant-peft is a chatbot model for dialogue generation. It was
 
 ## Model Details
 
-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. 
+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-v0.1/blob/main/finetune_falcon7b_oasst1_with_bnb_peft.ipynb) for the code and hyperparams used to train the model. 
 
 ### Model Date
 
@@ -45,7 +51,7 @@ To prompt the chat model, use the following format:
 <bot>:"""
 ```
 
-**falcon-7b-openassistant-peft**:
+**Falcon-7B-Chat-v0.1**:
 ```
 Dear friends,
 
@@ -65,7 +71,7 @@ Daniel
 <bot>:
 ```
 
-**falcon-7b-openassistant-peft**:
+**Falcon-7B-Chat-v0.1**:
 ```
 Here are some things to do in San Francisco:
 
@@ -120,7 +126,7 @@ from peft import PeftModel, PeftConfig
 from transformers import AutoModelForCausalLM, AutoTokenizer
 
 # load the model
-peft_model_id = "dfurman/falcon-7b-openassistant-peft"
+peft_model_id = "dfurman/Falcon-7B-Chat-v0.1"
 config = PeftConfig.from_pretrained(peft_model_id)
 
 model = AutoModelForCausalLM.from_pretrained(
@@ -173,7 +179,7 @@ print(generated_text.split("<human>: ")[1].split("<bot>: ")[-1])
 
 ## Reproducibility
 
-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. 
+See attached [Colab Notebook](https://huggingface.co/dfurman/Falcon-7B-Chat-v0.1/blob/main/finetune_falcon7b_oasst1_with_bnb_peft.ipynb) for the code (and hyperparams) used to train the model. 
 
 ### CUDA Info