Update README.md

README.md

@@ -1,199 +1,119 @@
----
-library_name: transformers
-tags: []
----
 
-# Model Card for Model ID
+```markdown
+# babelAI/opt-6.7b-lora
 
-<!-- Provide a quick summary of what the model is/does. -->
+## Model Description
 
+`babelAI/opt-6.7b-lora` is a variant of the OPT-6.7B model fine-tuned using LoRA (Low-Rank Adaptation) techniques. This model leverages the LoRA method to reduce the number of trainable parameters, allowing for efficient fine-tuning on domain-specific tasks without the need for extensive computational resources.
 
+## Model Architecture
 
-## Model Details
+- **Base Model**: OPT-6.7B
+- **Parameter Count**: 6.7 Billion
+- **Fine-Tuning Method**: LoRA (Low-Rank Adaptation)
 
-### Model Description
+## Intended Use
 
-<!-- Provide a longer summary of what this model is. -->
+This model is designed for a variety of natural language processing tasks, including but not limited to:
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+- Text generation
+- Text completion
+- Conversational AI
+- Language translation
 
-- **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]
+## How to Use
 
-### Model Sources [optional]
+### Installation
 
-<!-- Provide the basic links for the model. -->
+First, ensure you have the `transformers` library installed:
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+```bash
+pip install transformers
+```
 
-## Uses
+### Loading the Model
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+Here is an example of how to load and use the `babelAI/opt-6.7b-lora` model:
 
-### Direct Use
+```python
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from peft import PeftModel, PeftConfig
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+# Define the model ID
+peft_model_id = "babelAI/opt-6.7b-lora"
 
-[More Information Needed]
+# Load the configuration
+config = PeftConfig.from_pretrained(peft_model_id)
 
-### Downstream Use [optional]
+# Define the quantization configuration for efficient loading
+quantization_config = BitsAndBytesConfig(load_in_8bit=True)
 
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+# Load the base model with the quantization configuration
+model = AutoModelForCausalLM.from_pretrained(
+    config.base_model_name_or_path,
+    return_dict=True,
+    quantization_config=quantization_config,
+    device_map='auto'
+)
 
-[More Information Needed]
+# Load the tokenizer
+tokenizer = AutoTokenizer.from_pretrained(config.base_model_name_or_path)
 
-### Out-of-Scope Use
+# Load the LoRA model
+model = PeftModel.from_pretrained(model, peft_model_id)
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+# Example usage
+text = "Once upon a time"
+inputs = tokenizer(text, return_tensors='pt')
+outputs = model.generate(**inputs)
+generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
 
-[More Information Needed]
+print(generated_text)
+```
 
-## Bias, Risks, and Limitations
+## Training Data
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+The model was fine-tuned on a diverse set of texts to ensure robust performance across different domains. The dataset includes a mixture of publicly available text corpora, including:
 
-[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]
+- Wikipedia
+- Books
+- News articles
+- Conversational data
 
 ## 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]
+The model was evaluated on several benchmarks to ensure its performance is up to standard. Below are some of the evaluation metrics:
 
-**APA:**
+- Perplexity on common text datasets
+- Accuracy on specific language tasks
+- Performance on custom benchmarks relevant to specific use cases
 
-[More Information Needed]
+## Limitations and Biases
 
-## Glossary [optional]
+While `babelAI/opt-6.7b-lora` is a powerful model, it is important to be aware of its limitations:
 
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+- The model can generate biased or inappropriate content, reflecting biases present in the training data.
+- It may not perform well on highly specialized or niche topics without further fine-tuning.
 
-[More Information Needed]
+## Citation
 
-## More Information [optional]
+If you use this model in your research, please cite it as follows:
 
-[More Information Needed]
+```bibtex
+@misc{babelAI2024opt67blora,
+  author = {babelAI Team},
+  title = {babelAI/opt-6.7b-lora: A LoRA Fine-Tuned Model},
+  year = {2024},
+  howpublished = {\url{https://huggingface.co/babelAI/opt-6.7b-lora}},
+}
+```
 
-## Model Card Authors [optional]
+## License
 
-[More Information Needed]
+This model is licensed under the MIT License.
 
-## Model Card Contact
+## Contact Information
 
-[More Information Needed]
+For more information or questions, please contact the babelAI team at [babel.ai.dub@gmail.com].
+```