Update README.md

README.md

@@ -1,13 +1,17 @@
 ---
 base_model: gpt2
 library_name: peft
+datasets:
+- clemsadand/quote_data
+metrics:
+- bertscore
 ---
 
-# Model Card for Model ID
+# Model Card for Quote Generator
 
 <!-- Provide a quick summary of what the model is/does. -->
 
-
+This model is a fine-tuned version of GPT-2 using LoRA (Low-Rank Adaptation) to generate quotes based on a custom dataset. It is designed to create meaningful and inspirational quotes.
 
 ## Model Details
 
@@ -15,23 +19,23 @@ library_name: peft
 
 <!-- Provide a longer summary of what this model is. -->
 
+The Quote Generator is built on top of the GPT-2 model, fine-tuned using the Low-Rank Adaptation (LoRA) technique to specialize in generating quotes. The training dataset comprises a curated collection of quotes from various sources, enabling the model to produce high-quality and contextually relevant quotes.
 
+- **Developed by:** Clément Adandé
+<!-- - **Funded by [optional]:** N/A -->
+- **Shared by [optional]:** Clément Adandé
+- **Model type:** Language Model (NLP)
+- **Language(s) (NLP):** English
+- **License:** MIT
+- **Finetuned from model :** GPT-2
 
-- **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]
+### Model Sources
 
 <!-- Provide the basic links for the model. -->
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** [Quote Generator](https://huggingface.co/clemsadand/quote_generator/)
+<!-- - **Paper [optional]:** N/A -->
+<!-- - **Demo [optional]:** N/A -->
 
 ## Uses
 
@@ -41,162 +45,50 @@ library_name: peft
 
 <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
 
-[More Information Needed]
+The model can be directly used to generate quotes for various applications, such as social media content, motivational messages, and creative writing.
 
 ### 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]
+The model can be further fine-tuned for specific contexts or integrated into applications requiring quote generation.
 
 ### Out-of-Scope Use
 
 <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
 
-[More Information Needed]
+The model should not be used for generating harmful, offensive, or misleading content. It may not perform well for generating quotes in languages other than English.
 
 ## Bias, Risks, and Limitations
 
 <!-- This section is meant to convey both technical and sociotechnical limitations. -->
 
-[More Information Needed]
+The model may inherit biases present in the training data. Generated quotes may not always be factually accurate or appropriate for all contexts. Users should verify the content before use in sensitive applications.
 
 ### 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.
+Users (both direct and downstream) should be made aware of the risks, biases, and limitations of the model. It is recommended to review and edit the generated quotes before public use.
 
 ## 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]
+```python
+from peft import PeftModel, PeftConfig
+from transformers import AutoModelForCausalLM
 
-## Model Card Authors [optional]
+config = PeftConfig.from_pretrained("clemsadand/quote_generator")
+base_model = AutoModelForCausalLM.from_pretrained("gpt2")
+model = PeftModel.from_pretrained(base_model, "clemsadand/quote_generator")
 
-[More Information Needed]
+tokenizer = AutoTokenizer.from_pretrained("gpt2")
 
-## Model Card Contact
+input_text = "Generate a quote about kindness with the keywords compassion, empathy, help, generosity, care"
+input_ids = tokenizer.encode(input_text, return_tensors="pt")
 
-[More Information Needed]
-### Framework versions
+output = model.generate(input_ids)
+generated_text = tokenizer.decode(output[0], skip_special_tokens=True)
 
-- PEFT 0.11.1
+print(generated_text)