Update README.md

README.md

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 ---
+library_name: peft
 license: apache-2.0
+pipeline_tag: text-classification
+tags:
+- hatespeech
+- hatecot
+- cot
+- llama
 ---
+
+## Introduction
+This is the LoRA-adapater for the Llama-13B introduced in the paper 
+*HateCOT: An Explanation-Enhanced Dataset for Generalizable Offensive Speech Detection via Large Language Models*.
+The base model is instruction-finetuned on 52,000 samples that includes augmented humman annotation to produce 
+legible explanations based on predefined criteria in the **provided definition**.
+
+
+To use the model, please load along with the original Llama model (detailed configuration in the *Training Procedure*). 
+For instruction to load Peft models: https://huggingface.co/docs/transformers/main/en/peft
+
+These adapters can also be finetuned on a new set of data. See the article for more details.
+
+## Usage
+Use the following template to prompt the model:
+```
+### Instruction
+Perform this task by considering the following Definitions.
+Based on the message, label the input as only one of the following categories:
+[Class 1], [Class 2], ..., or [Class N].
+Provide a brief paragraph to explain step-by-step why the post should be classsified
+with the provided Label based on the given Definitions. If this post targets a group or
+entity relevant to the definition of the specified Label, explain who this target is and how
+that leads to that Label.
+Append the string '<END>' to the end of your response. Provide your response in the following format:
+EXPLANATION: [text]
+LABEL:[text] <END>
+### Definitions:
+[Class 1]: [Definition 1]
+[Class 2]: [Definition 2]
+...
+[Class N]: [Definition 3]
+### Input
+{post}
+### Response:
+```
+
+## Citation
+```bibtex
+@article{nghiem2024hatecot,
+  title={HateCOT: An Explanation-Enhanced Dataset for Generalizable Offensive Speech Detection via Large Language Models},
+  author={Nghiem, Huy and Daum{\'e} III, Hal},
+ journal={arXiv preprint arXiv:2403.11456},
+  year={2024}
+}
+```
+
+## Original Model
+Please visit the main repository to gain permission to download original model weights.
+
+https://huggingface.co/meta-llama
+
+
+
+## Training procedure
+
+
+The following `bitsandbytes` quantization config was used during training:
+- quant_method: bitsandbytes
+- load_in_8bit: True
+- load_in_4bit: False
+- llm_int8_threshold: 6.0
+- llm_int8_skip_modules: None
+- llm_int8_enable_fp32_cpu_offload: False
+- llm_int8_has_fp16_weight: False
+- bnb_4bit_quant_type: nf4
+- bnb_4bit_use_double_quant: False
+- bnb_4bit_compute_dtype: float16
+### Framework versions
+
+
+- PEFT 0.5.0