malhajar
/

Shahin-v0.1

@@ -1,199 +1,101 @@
 ---
 library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
 ## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
-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]
-### 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]
-## 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]

 ---
 library_name: transformers
+language:
+- ar
 ---
+<img src="https://example.com/shahin-logo.png" alt="Shahin-v0.1" width="400"/>
+# Shahin-v0.1
+**Shahin-v0.1** is a large language model (LLM) created specifically for the Syrian Arabic dialect, designed as a tribute to the resilience and spirit of the Syrian people. This model is a beacon of freedom and progress, developed in honor of their victory against 70 years of dictatorship. It offers unparalleled fluency in Syrian Arabic and excels in a wide range of tasks, from dialogue generation to cultural insights, history, and more.
 ## Model Details
+- **Model Base**: Custom architecture with 13 billion parameters, optimized for Syrian Arabic
+- **Languages Supported**: Primarily Syrian Arabic, with basic support for Modern Standard Arabic (MSA)
+- **Training Data**: A comprehensive corpus of Syrian Arabic, including spoken language, literature, historical archives, and user-generated content
+- **Hardware & Training**: Fine-tuned on 4 NVIDIA A100 GPUs over 3 days with specialized datasets
+## Key Features
+- **Syrian Dialect Mastery**: Designed to capture the nuances of Syrian Arabic, including regional variations and idiomatic expressions.
+- **Cultural Sensitivity**: Trained on data reflecting Syrian heritage, customs, and history to generate culturally aware responses.
+- **Wide Application**: Excels in conversational AI, content creation, historical analysis, and educational tasks.
+## Example Usage
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+device = "cuda"
+model_name = "malhajar/Shahin-v0.1"
+model = AutoModelForCausalLM.from_pretrained(
+    model_name,
+    torch_dtype="auto",
+    device_map="auto"
+)
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+prompt = "شو الأسباب يلي خلت الثورة السورية تستمر رغم كل الظروف؟"
+messages = [
+    {
+        "role": "system",
+        "content": "أنت مساعد افتراضي سوري، جاهز للإجابة على الأسئلة بكل وضوح وصدق."
+    },
+    {
+        "role": "user",
+        "content": prompt
+    }
+]
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True
+)
+model_inputs = tokenizer([text], return_tensors="pt").to(device)
+generated_ids = model.generate(
+    model_inputs.input_ids,
+    temperature=0.7,
+    top_k=40,
+    top_p=0.85,
+    max_new_tokens=256,
+    repetition_penalty=1.1,
+)
+response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+print(response)
+```
+## Example Outputs
+### Example 1
+**Prompt:**
+```
+شو الأسباب يلي خلت الثورة السورية تستمر رغم كل الظروف؟
+```
+**Response:**
+الثورة السورية استمرت بفضل إصرار الشعب السوري على الحرية والكرامة. الشعب ما تخلى عن مطالبه رغم القمع العنيف والظروف الصعبة، وكان في دعم كبير من المغتربين السوريين . الإرادة الحقيقية لتغيير الواقع المظلم كانت أقوى من أي تحدي.
+### Example 2
+**Prompt:**
+```
+احكيلي عن تاريخ قلعة حلب.
+```
+**Response:**
+قلعة حلب هي واحدة من أهم المعالم التاريخية بسوريا، عمرها يرجع لأكثر من 4,000 سنة. كانت مركزاً للدفاع عن المد��نة ومرت عليها حضارات عديدة مثل الحثيين، الرومان، والأيوبيين. اليوم، هي رمز للصمود السوري ومرآة لتاريخ الشعب العريق.
+---
+Shahin-v0.1 showcases the beauty and strength of Syrian Arabic and stands as a technological milestone for the Syrian people.
+---