| # Model Card for olsi8/gemma-3-4b-it-shqip-v1 | |
| ### Model Details | |
| **Model Description** | |
| This model, identified as olsi8/gemma-3-4b-it-shqip-v1, is a 🤗 Transformers model hosted on the Hugging Face Hub. It represents a fine-tuned iteration of the gemma-3-4b-it model, specifically adapted for the Albanian language (Shqip). The primary purpose of this model is text generation, leveraging the underlying capabilities of the Gemma architecture. This model card provides an overview of its development, intended uses, and other relevant details. | |
| **Developed by:** | |
| The model was developed by the Hugging Face user olsi8. | |
| **Funded by:** | |
| Information regarding funding for this specific fine-tuning effort is not explicitly provided. | |
| **Shared by:** | |
| The model is shared by the Hugging Face user olsi8. | |
| **Model type:** | |
| This is a large language model (LLM) based on the Gemma architecture. It is designed for text generation tasks and has been fine-tuned from the `gemma-3-4b-it` model. The tags on its Hugging Face page include "Image-Text-to-Text", "Transformers", "gemma3", and "text-generation-inference", indicating its capabilities and framework. | |
| **Language(s) (NLP):** | |
| The primary language supported by this model is Albanian (Shqip). Given its base model, it may retain some capabilities in English, though its fine-tuning focus is on Albanian. | |
| **License:** | |
| The license for this specific fine-tuned model is not explicitly stated on its Hugging Face page. It is likely to inherit the license of the base model, `gemma-3-4b-it`, which is typically governed by the Gemma Terms of Use. Users should verify the licensing terms before use. | |
| **Finetuned from model:** | |
| This model was fine-tuned from `google/gemma-3-4b-it`. | |
| ### Model Sources | |
| **Repository:** | |
| The model is hosted on the Hugging Face Model Hub. The repository can be found at [https://huggingface.co/olsi8/gemma-3-4b-it-shqip-v1](https://huggingface.co/olsi8/gemma-3-4b-it-shqip-v1). | |
| **Paper:** | |
| There is no specific paper associated with this fine-tuned model. However, for information on the base Gemma models, users can refer to the relevant Google publications. | |
| **Demo:** | |
| No specific demo is provided for this model on its Hugging Face page. | |
| ### Uses | |
| **Direct Use:** | |
| This model is intended for direct use in generating text in the Albanian language. It can be employed for tasks such as content creation, translation assistance (from other languages to Albanian, with caution), and as a foundational tool for further fine-tuning on more specific Albanian NLP tasks. Due to its proof-of-concept nature, extensive testing is recommended before deployment in production environments. | |
| **Downstream Use:** | |
| The model can serve as a base for further fine-tuning on specialized Albanian language datasets for tasks like sentiment analysis, question answering, or domain-specific text generation. | |
| **Out-of-Scope Use:** | |
| This model is not intended for generating harmful, biased, or misleading content. It should not be used for critical decision-making without human oversight, especially given its current stage as a proof-of-concept. Use in languages other than Albanian is not its primary design and may yield suboptimal results. | |
| ### Bias, Risks, and Limitations | |
| As with all large language models, olsi8/gemma-3-4b-it-shqip-v1 may inherit biases present in its training data, which includes books and the `olsi8/albanian-lang-gemma-format` dataset. These biases could manifest in the generated text. The model's performance is limited by the scope and quality of its training data; it may generate incorrect or nonsensical information (hallucinations). Given that it is a proof-of-concept, its robustness and generalization capabilities might be limited compared to more extensively trained models. The mean token accuracy of 0.77 on the `olsi8/albanian-lang-gemma-format` dataset indicates that while it has learned the task to a degree, there is still room for improvement and potential for errors. | |
| ### Recommendations | |
| Users (both direct and downstream) should be made aware of the risks, biases, and limitations of the model. It is strongly recommended to thoroughly evaluate the model's outputs for any specific application. Human oversight is crucial when using the model for any sensitive tasks. Users should also note that this model is considered a proof of concept and has been superseded by newer versions or alternative approaches, as indicated by its deprecated status. For production use, exploring more mature and extensively evaluated models is advised. | |
| ### How to Get Started with the Model | |
| To get started with the `olsi8/gemma-3-4b-it-shqip-v1` model, you can use the Hugging Face Transformers library. Below is an example of how to load the model and tokenizer and generate text. Ensure you have the `transformers` and `torch` libraries installed. | |
| ```python | |
| from transformers import AutoTokenizer, AutoModelForCausalLM | |
| model_id = "olsi8/gemma-3-4b-it-shqip-v1" | |
| # Load tokenizer and model | |
| tokenizer = AutoTokenizer.from_pretrained(model_id) | |
| model = AutoModelForCausalLM.from_pretrained(model_id) | |
| # Prepare your input prompt (example in Albanian) | |
| input_text = "Përshëndetje, mundeni të më ndihmoni me planifikimin e ditës time të sotme?" | |
| input_ids = tokenizer(input_text, return_tensors="pt").input_ids | |
| # Generate text | |
| # Note: You might need to adjust generation parameters like max_length, num_beams, etc. | |
| # based on your specific needs and the model's capabilities. | |
| outputs = model.generate(input_ids, max_length=50) | |
| # Decode and print the generated text | |
| print(tokenizer.decode(outputs[0], skip_special_tokens=True)) | |
| ``` | |
| It is important to note that since this model is a proof-of-concept and marked as deprecated, users should exercise caution and consider more recent or robust models for production applications. The example above provides a basic framework; further customization of generation parameters will likely be necessary for optimal results. | |
| ### Training Details | |
| **Training Data** | |
| The model `olsi8/gemma-3-4b-it-shqip-v1` was fine-tuned on a combination of Albanian language data. This included a collection of books and the specific dataset `olsi8/albanian-lang-gemma-format`, which is available on Hugging Face at [https://huggingface.co/datasets/olsi8/albanian-lang-gemma-format](https://huggingface.co/datasets/olsi8/albanian-lang-gemma-format). The nature of the books used is not specified in detail, but they contributed to the Albanian language corpus for training. | |
| **Training Procedure** | |
| *Preprocessing* | |
| Details regarding the specific preprocessing steps applied to the training data are not extensively documented on the model card. Standard preprocessing for language models typically includes tokenization, formatting of input-output pairs, and potentially data cleaning or filtering. Given the use of the `albanian-lang-gemma-format` dataset, it is likely that the data was structured to be compatible with the Gemma model's training requirements. | |
| *Training Hyperparameters* | |
| Specific training hyperparameters such as learning rate, batch size, number of epochs, and optimization algorithms used for fine-tuning `olsi8/gemma-3-4b-it-shqip-v1` are not detailed on its Hugging Face page. The training regime would have involved fine-tuning the pre-trained `gemma-3-4b-it` model on the aforementioned Albanian language data. | |
| *Speeds, Sizes, Times* | |
| Information about the training speed, computational resources utilized, and total training time for this specific fine-tuning effort is not provided. | |
| ### Evaluation | |
| **Testing Data, Factors & Metrics** | |
| *Testing Data* | |
| The model was evaluated on the `olsi8/albanian-lang-gemma-format` dataset. Information about other specific testing datasets or benchmarks used for a broader evaluation is not readily available. | |
| *Factors* | |
| Key factors influencing the model's performance include the size and quality of the Albanian language data it was fine-tuned on, the architecture of the base `gemma-3-4b-it` model, and the specific fine-tuning process. The model's capabilities are primarily focused on the Albanian language. | |
| *Metrics* | |
| The primary metric reported for this model is an accuracy of 0.77 on the `olsi8/albanian-lang-gemma-format` dataset. Other standard NLP evaluation metrics (e.g., perplexity, BLEU scores for translation-like tasks, ROUGE for summarization, etc.) are not explicitly provided for this model on its Hugging Face page. | |
| **Results** | |
| The reported accuracy of 0.77 on the specified dataset indicates a degree of success in learning the target task for the Albanian language. However, as a proof-of-concept model, these results should be interpreted with caution, and further evaluation on diverse benchmarks would be necessary to fully understand its performance characteristics. | |
| **Summary** | |
| `olsi8/gemma-3-4b-it-shqip-v1` demonstrates foundational capabilities in Albanian language processing, achieving a notable accuracy on its fine-tuning dataset. Nevertheless, its status as a proof-of-concept and deprecated model suggests that it serves more as an experimental iteration than a production-ready solution. | |
| ### Model Examination | |
| Further examination of the model's outputs, error analysis, and performance on specific linguistic phenomena in Albanian would be beneficial for a deeper understanding of its strengths and weaknesses. Such detailed examination is not provided in the current model card. | |
| ### Technical Specifications | |
| **Model Architecture and Objective** | |
| The model utilizes the Gemma architecture, specifically the `gemma-3-4b-it` version, which has approximately 3.4 billion parameters. The objective of this fine-tuned version is causal language modeling, tailored for generating coherent and contextually relevant text in the Albanian language. | |
| **Compute Infrastructure** | |
| *Hardware* | |
| Specific hardware used for the fine-tuning process is not detailed. Training models of this size typically requires access to high-performance GPUs. | |
| *Software* | |
| The model was developed using the Hugging Face Transformers library. Other common software includes PyTorch or TensorFlow, CUDA for GPU acceleration, and various Python libraries for data processing. | |
| ### Citation | |
| **BibTeX:** | |
| As this is a fine-tuned model by a community user, a specific BibTeX entry for this exact model version may not exist. For the base Gemma models, refer to Google's official publications. A general citation for the model repository could be: | |
| ```bibtex | |
| @misc{olsi8_gemma_3_4b_it_shqip_v1, | |
| author = {olsi8}, | |
| title = {gemma-3-4b-it-shqip-v1: A fine-tuned Gemma model for Albanian}, | |
| year = {2024}, | |
| publisher = {Hugging Face}, | |
| journal = {Hugging Face repository}, | |
| howpublished = {\url{https://huggingface.co/olsi8/gemma-3-4b-it-shqip-v1}} | |
| } | |
| ``` | |
| **APA:** | |
| olsi8. (2024). *gemma-3-4b-it-shqip-v1: A fine-tuned Gemma model for Albanian*. Hugging Face. Retrieved from https://huggingface.co/olsi8/gemma-3-4b-it-shqip-v1 | |
| ### Glossary | |
| [More Information Needed - A glossary could define terms like "fine-tuning", "causal language modeling", "Gemma architecture", etc., if deemed necessary for the audience.] | |
| ### More Information | |
| This model, `olsi8/gemma-3-4b-it-shqip-v1`, should be considered a proof-of-concept for fine-tuning Gemma models for the Albanian language. It has been marked as **deprecated**. Users are advised that newer, potentially more robust models or alternative approaches may be available and should be preferred for ongoing development or production use. The model was trained on a combination of books and the `olsi8/albanian-lang-gemma-format` dataset. | |
| ### Model Card Authors | |
| This model card was generated by an AI assistant based on publicly available information and user-provided details. The original model was developed and shared by the Hugging Face user 'olsi8'. | |
| ### Model Card Contact | |
| For questions or issues regarding the model itself, contacting the model owner 'olsi8' through their Hugging Face profile ([https://huggingface.co/olsi8](https://huggingface.co/olsi8)) would be the most direct approach. For issues with this model card, please refer to the generating entity. | |