Update README.md

README.md

@@ -3,200 +3,73 @@ base_model: unsloth/gemma-2-2b-it
 library_name: peft
 ---
 
-# Model Card for Model ID
+## Model Summary
 
-<!-- Provide a quick summary of what the model is/does. -->
+This model is fine-tuned from gemma-2-2b-it using a custom dataset created by our team, providing a concise overview of its key details and purpose.
 
 
+## Motivation
 
-## Model Details
+Women's health is a critical and often underserved topic, with limited accessible resources where women can ask questions and receive reliable answers about their health. Recognizing this gap, we embarked on this project to develop a compact language model (LLM) tailored to address these needs. Our goal is to create a model that not only provides valuable insights but also enables efficient on-device inference, ensuring greater accessibility and usability for women worldwide.
 
-### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
+## Usage
 
+```
+model, tokenizer = FastLanguageModel.from_pretrained(
+    model_name=model_path,
+    max_seq_length=max_seq_length,
+    dtype=dtype,
+    load_in_4bit=load_in_4bit,
+)
+FastLanguageModel.for_inference(model) 
 
+text_streamer = TextStreamer(tokenizer, skip_prompt = True)
 
-- **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]
+tokenizer = AutoTokenizer.from_pretrained('unsloth/gemma-2-2b-it')
 
-### Model Sources [optional]
 
-<!-- Provide the basic links for the model. -->
+messages = [
+    #{"role": "system", "content": system_prompt},
+    {"role": "user", "content": user_prompt},
+]
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
 
-## Uses
+input_ids = tokenizer.apply_chat_template(
+    messages,
+    tokenize = True,
+    add_generation_prompt = True,
+    return_tensors = "pt",
+).cuda()
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+terminators = [tokenizer.eos_token_id, tokenizer.convert_tokens_to_ids("<end_of_turn>")]
 
-### Direct Use
+#input_ids = tokenizer(wiki, return_tensors="pt").input_ids.cuda()
+outputs = model.generate(input_ids = input_ids,
+    streamer = text_streamer if use_streamer else None,
+    max_new_tokens = 1024,
+    eos_token_id=terminators,
+    use_cache=True, do_sample=True, temperature=0.6, top_p=0.9)
+if not use_streamer:
+    out = outputs[0][input_ids.shape[-1]:]
+    generated_text = tokenizer.decode(out, skip_special_tokens=True)
+    print(generated_text)
 
-<!-- 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]
+## Dataset
 
-### Out-of-Scope Use
+The dataset was prepared through a comprehensive process to ensure quality and relevance. Health-related websites were scraped, open-source e-books and PDFs focusing on women's health were collected, and an instruction dataset was created from these sources. To generate high-quality questions, we utilized the gemini-flash model, ensuring the dataset’s alignment with the domain.
+The dataset will be made publicly available through its dedicated repository [altaidevorg/women-health-mini](https://huggingface.co/datasets/altaidevorg/women-health-mini). Additionally, the code used for dataset generation will be released in the future to promote transparency and enable reproducibility.
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+## Evaluation Notes
 
-[More Information Needed]
+During testing, we observed that the LoRA checkpoint performed better in evaluations compared to the version where the LoRA checkpoint was merged with the base model. Interestingly, the standalone LoRA checkpoint consistently delivered superior results, though we currently lack a concrete explanation for this phenomenon.
+We are actively investigating the underlying cause, with our best hypothesis being that the merging process may introduce some form of precision loss. Further research is underway to validate this theory and optimize the performance.
 
-## Bias, Risks, and Limitations
+### Disclaimer
 
-<!-- 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]
-
-## 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 0.13.0
+Any output of this model should never be taken as a medical advice, and it is mainly intended for research purposes.