Update README.md

README.md

@@ -1,199 +1,160 @@
 ---
 library_name: transformers
-tags: []
+tags:
+- roblox
+- luau
+- code-generation
+- fine-tuning
+license: apache-2.0
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
+# Model Card for Roblox-Coder-Llama-7B-v1
 
+This model is a fine-tuned version of `codellama/CodeLlama-7b-instruct-hf`, specialized in generating and understanding Luau code for development on the Roblox platform. It has been trained on a custom dataset of instructions and responses in Spanish and English, with the goal of acting as an expert programming assistant for Roblox creators.
 
 ## 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]
+`Roblox-Coder-Llama-7B-v1` is a language model designed to assist Roblox developers. It can generate Luau scripts from natural language descriptions, explain complex concepts of the Roblox API, and help optimize code. The goal of this project is to democratize game development on Roblox, making it more accessible for beginners and more efficient for experienced developers.
 
-### Model Sources [optional]
+- **Developed by:** Sergio Belenguer, with the assistance of a conversational AI.
+- **Shared by:** Sergio Belenguer (Hash0x)
+- **Model type:** Causal Language Model (CLM)
+- **Language(s) (NLP):** Spanish (es), English (en), Luau (code)
+- **License:** Apache 2.0
+- **Finetuned from model:** `codellama/CodeLlama-7b-instruct-hf`
 
-<!-- Provide the basic links for the model. -->
+### Model Sources
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+- **Repository:** `https://huggingface.co/Hash0x/Roblox-Coder-Llama-7B-v1`
+- **Dataset Used:** `https://huggingface.co/datasets/Hash0x/Roblox-Luau-Instruct-V1`
 
 ## 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]
+This model is intended for direct use via a `text-generation` pipeline for:
+- **Code Generation:** Asking it to write complete scripts or specific functions in Luau.
+- **Tutoring and Explanation:** Asking questions about how Roblox APIs work (`DataStoreService`, `CFrame`, etc.).
+- **Debugging:** Asking it to find errors or suggest improvements in existing code snippets.
 
 ### 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 the foundation for creating more complex tools, such as:
+- A Roblox Studio plugin that acts as a "Copilot" for Roblox.
+- A Discord bot for a developer community server.
+- A Visual Studio Code extension offering intelligent autocompletion and suggestions for Luau.
 
 ### Out-of-Scope Use
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
+This model should not be used to generate malicious code, exploits, or scripts that violate the Roblox Terms of Service. The generated code must always be reviewed by a human, as it may contain unintentional errors or vulnerabilities.
 
 ## Bias, Risks, and Limitations
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
+The model was trained on a limited dataset, which entails certain risks and limitations:
+- **Dataset Bias:** The model's knowledge is limited to the examples in the training dataset. It may have poor knowledge of areas of the Roblox API that were not well-represented.
+- **Hallucinations:** The model may invent functions or methods that do not exist in Luau.
+- **Context Contamination:** Due to the base model's pre-trained knowledge, it may occasionally become confused and generate code in other video game programming languages (like C# for Unity), especially if the instruction is ambiguous or the fine-tuning dataset is not large enough.
 
 ### 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.
+**Never blindly trust the generated code!** Treat the model as a very fast junior assistant. Always review, understand, and test the code it produces before implementing it in a real project. The best way to improve the model is by expanding the training dataset with more high-quality examples.
 
 ## How to Get Started with the Model
 
-Use the code below to get started with the model.
+Use the code below to get started with the model using the `transformers` library.
 
-[More Information Needed]
+```python
+import torch
+from transformers import pipeline
 
-## Training Details
+# Make sure you are logged in with your HF token
+# from huggingface_hub import login
+# login()
 
-### Training Data
+pipe = pipeline(
+    "text-generation",
+    model="Hash0x/Roblox-Coder-Llama-7B-v1",
+    torch_dtype="auto",
+    device_map="auto"
+)
 
-<!-- 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. -->
+prompt = "Create a script that makes a part spin constantly on its Y-axis."
+# CodeLlama uses a specific prompt format
+formatted_prompt = f"<s>[INST] {prompt} [/INST]"
 
-[More Information Needed]
+result = pipe(
+    formatted_prompt,
+    max_new_tokens=512,
+    do_sample=True,
+    temperature=0.7,
+    top_k=50,
+    top_p=0.95
+)
 
-### Training Procedure
+print(result[0]['generated_text'])
+```
 
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+## Training Details
 
-#### Preprocessing [optional]
+### Training Data
 
-[More Information Needed]
+The model was trained using the `Hash0x/Roblox-Luau-Instruct-V1` dataset. This dataset was created from several sources:
+- **Official Roblox Documentation:** Code samples and API explanations rewritten in an instruction format.
+- **Open-Source Projects:** Code snippets from GitHub repositories with permissive licenses.
+- **Developer Community:** Inspiration from real-world problems and solutions on the Roblox Developer Forum.
 
+### Training Procedure
 
-#### Training Hyperparameters
+The model was fine-tuned using the **QLoRA** (Quantized Low-Rank Adaptation) technique to make training efficient on a single GPU.
 
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+#### Preprocessing
 
-#### Speeds, Sizes, Times [optional]
+The instructions and responses from the dataset were formatted into a prompt that follows the format expected by the base model: `<s>[INST] {instruction} [/INST] {output}`.
 
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+#### Training Hyperparameters
 
-[More Information Needed]
+- **`per_device_train_batch_size`**: 1
+- **`gradient_accumulation_steps`**: 4 (effective batch size of 4)
+- **`learning_rate`**: 2e-4
+- **`num_train_epochs`**: 1-3
+- **`optim`**: paged_adamw_32bit
+- **QLoRA `r`**: 64
+- **QLoRA `alpha`**: 16
 
 ## 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]
+The model's evaluation to date has been qualitative, testing its ability to respond to a variety of prompts and analyzing the quality of the generated code. No formal quantitative evaluation with standard metrics has been performed.
 
 ## 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]
+- **Hardware Type:** NVIDIA T4
+- **Hours used:** ~1-2 hours (including experimentation and troubleshooting)
+- **Cloud Provider:** Google Colab
+- **Compute Region:** Variable (assigned by Google)
+- **Carbon Emitted:** Low estimate due to the use of QLoRA and a moderately-powered GPU.
 
 ## Technical Specifications [optional]
 
 ### Model Architecture and Objective
 
-[More Information Needed]
+The base model, `codellama/CodeLlama-7b-instruct-hf`, is a Causal Language Model based on the Llama 2 architecture. The fine-tuning objective was Causal Language Modeling optimization for Luau code generation.
 
 ### Compute Infrastructure
 
-[More Information Needed]
-
 #### Hardware
-
-[More Information Needed]
+Training was performed in the Google Colab environment, using a single NVIDIA T4 GPU with ~15 GB of VRAM.
 
 #### Software
+- **Libraries:** `transformers`, `datasets`, `accelerate`, `peft`, `bitsandbytes`, `trl`.
+- **Framework:** PyTorch
+- **Environment:** Google Colaboratory
 
-[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]
+## Model Card Authors
 
-[More Information Needed]
+- **Sergio Belenguer (Hash0x)**
 
 ## Model Card Contact
 
-[More Information Needed]
+For questions or feedback, please contact through the Hash0x Hugging Face profile.