Update README.md

README.md

@@ -1,15 +1,24 @@
 ---
 library_name: transformers
-tags: []
+tags:
+- text-generation-inference
+license: cc-by-4.0
+datasets:
+- AhmadMustafa/Urdu-Instruct-News-Article-Generation
+language:
+- ur
 ---
 
 # Model Card for Model ID
 
-<!-- Provide a quick summary of what the model is/does. -->
+This is Instruct Fine-tuned Version of [MobiLlama](https://arxiv.org/abs/2402.16840) Fine-tuned on [Instruct Urdu Article Generation Dataset](https://huggingface.co/datasets/AhmadMustafa/Urdu-Instruct-News-Article-Generation). Instruct Urdu Article Generation Dataset was released under [AYA Collections](https://arxiv.org/abs/2402.06619) by [Cohere for AI](cohere.for.ai)
 
+This model is finetuned for 8500 steps for generating articles in Urdu Language.
 
 
-## Model Details
+Fine-Tuning Statistics:
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/6246908d8031dcfa9ef6d80b/Y9t_6KZ8Uloe0N16yqTPk.png)
+
 
 ### Model Description
 
@@ -17,185 +26,65 @@ tags: []
 
 This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
 
-- **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]
+- **Developed by:** [Ahmad Mustafa Anis]
+- **Language(s) (NLP):** [Urdu]
+- **License:** [CC by 4.0]
+- **Finetuned from model [optional]:** [MBZUAI/MobiLlama-05B]
 
 ### Model Sources [optional]
 
 <!-- Provide the basic links for the model. -->
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** [https://github.com/mbzuai-oryx/MobiLlama?tab=readme-ov-file]
+- **Paper [optional]:** [https://arxiv.org/abs/2402.16840]
 
 ## Uses
-
+This model is intended to use on mobile devices for generating articles in Urdu Language.
 <!-- 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.
+This model may contain biases and limitations that are present in LLMs and I have not accounted for them.
 
 ## 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. -->
+```python3
 
-[More Information Needed]
+model = AutoModelForCausalLM.from_pretrained("AhmadMustafa/Mobile-LLama-Urdu-Article-Generation", trust_remote_code=True).to(device)
+tokenizer = AutoTokenizer.from_pretrained("MBZUAI/MobiLlama-05B")
 
-#### Factors
+example = {'inputs': """ اس دی گی ایک خبر سے متعلق ایک مضمون لکھیں۔
+خبر: سشانت سنگھ کیس بھارتی سپریم کورٹ نے فریقین سے مفصل جواب طلب کرلیا""",
+}
 
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+example = f"### Instruction: {example['inputs']}\n ### Completion: "
+inputs = tokenizer.encode(f"{example}", return_tensors="pt").to(device)
 
-[More Information Needed]
+outputs = model.generate(inputs, max_new_tokens=512)
 
-#### 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]
+print(tokenizer.decode(outputs[0]))
+```
 
+Please note that I have used <|EOS|> in the end of each example so you can use that as ending token to control generation.
 ## 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]
+@misc{thawakar2024mobillama,
+      title={MobiLlama: Towards Accurate and Lightweight Fully Transparent GPT}, 
+      author={Omkar Thawakar and Ashmal Vayani and Salman Khan and Hisham Cholakkal and Rao Muhammad Anwer and Michael Felsberg and Timothy Baldwin and Eric P. Xing and Fahad Shahbaz Khan},
+      year={2024},
+      eprint={2402.16840},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL}
+} 
 
 ## Model Card Authors [optional]
 
-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]
-
-
+- Name: Ahmad Mustafa Anis
+- Email: [email protected]