Update README.md

README.md

@@ -1,202 +1,117 @@
 ---
-base_model: Qwen/Qwen2.5-7B-Instruct
+language:
+- en
+- ko
+tags:
+- qwen
+- lora
+- rag
+- instruction-tuning
+- email
+- qwen-2.5
+- peft
+- question-answering
 library_name: peft
+pipeline_tag: text-generation
+license: mit
 ---
 
-# Model Card for Model ID
+# Qwen-RAG-LoRA
 
-<!-- Provide a quick summary of what the model is/does. -->
+This repository contains LoRA weights for [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct), fine-tuned for email-based question answering tasks. The model has been trained to handle both English and Korean queries about email content.
 
+## Model Description
 
-
-## Model Details
-
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
-
-
-
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
-
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
+- **Base Model:** Qwen/Qwen2.5-7B-Instruct
+- **Training Type:** LoRA (Low-Rank Adaptation)
+- **Checkpoint:** checkpoint-600
+- **Languages:** English and Korean
+- **Task:** Email-based Question Answering
+- **Domain:** Email Content
 
 ## Training Details
 
-### Training Data
-
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
-
-[More Information Needed]
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]
-### Framework versions
-
-- PEFT 0.14.0
+### LoRA Configuration
+```python
+lora_config = LoraConfig(
+    r=8,
+    lora_alpha=32,
+    target_modules=["q_proj", "k_proj", "v_proj", "o_proj", "gate_proj", "up_proj", "down_proj"],
+    lora_dropout=0.1,
+    bias="none",
+    task_type="CAUSAL_LM"
+)
+```
+
+## Usage with vLLM
+
+```python
+from vllm import LLM, SamplingParams
+from vllm.lora.request import LoRARequest
+
+# Initialize LLM with LoRA support
+llm = LLM(
+    model="Qwen/Qwen2.5-7B-Instruct",
+    tensor_parallel_size=2,
+    enable_lora=True
+)
+
+sampling_params = SamplingParams(temperature=0.0, max_tokens=50)
+
+# Create LoRA request
+lora_request = LoRARequest(
+    "rag_adapter",
+    1,
+    "doubleyyh/qwen-rag-lora"  # HuggingFace repo name
+)
+
+# Example prompt
+prompt = """Using the context provided below, answer the question concisely. Respond in Korean if the question is in Korean, and in English if the question is in English.
+
+Context: subject: Meeting Schedule Update
+from: [['John Smith', '[email protected]']]
+to: [['Team', 'team@company.com']]
+text_body: The project review meeting is rescheduled to 3 PM tomorrow.
+
+Question: When is the meeting rescheduled to?
+
+Answer: """
+
+# Generate with LoRA
+outputs = llm.generate([prompt], sampling_params, lora_request=lora_request)
+print(outputs[0].outputs[0].text)
+```
+
+## Example Input/Output
+
+```
+# English Query
+Q: When is the project review scheduled?
+A: The project review meeting is rescheduled to 3 PM tomorrow.
+
+# Korean Query
+Q: 프로젝트 미팅이 언제로 변경되었나요?
+A: 내일 오후 3시로 변경되었습니다.
+```
+
+## Limitations
+
+- The model is specifically trained for email-related queries
+- Performance might vary between English and Korean
+- Optimal results when used with email content in standard format
+- Limited to the capabilities of the base Qwen model
+
+## Citation
+
+```bibtex
+@misc{qwen-rag-lora,
+  author = {doubleyyh},
+  title = {Qwen-RAG-LoRA: Fine-tuned LoRA Weights for Email QA},
+  year = {2024},
+  publisher = {Hugging Face}
+}
+```
+
+## License
+
+This model follows the same license as Qwen2.5-7B-Instruct.