Upload folder using huggingface_hub

README.md

@@ -1,69 +1,210 @@
 ---
-language:
-  - bg
-  - en
-license: mit
-base_model: Qwen/Qwen2.5-Coder-7B-Instruct
+base_model: unsloth/Qwen2.5-Coder-7B-Instruct
+library_name: peft
+pipeline_tag: text-generation
 tags:
-  - code
-  - bulgarian
-  - lora
-  - peft
-  - vitosha-gpt-code
-  - slm
-  - offline
+- base_model:adapter:unsloth/Qwen2.5-Coder-7B-Instruct
+- lora
+- sft
+- transformers
+- trl
+- unsloth
 ---
 
-# Vitosha-GPT-Code
+# Model Card for Model ID
 
-**Every Bulgarian has the right to AI.** Right now that’s a luxury for people with fast internet and expensive hardware. If you’re in a remote area on an old PC, you’re locked out. Vitosha-GPT-Code is built to change that.
+<!-- Provide a quick summary of what the model is/does. -->
 
-It’s a **Bulgarian-first coding assistant** (Small Language Model / SLM track): explanations and code in Bulgarian by default. Named after Vitosha, the mountain overlooking Sofia. The goal is to run **100% offline on as little as 4GB RAM**—no subscriptions, no fiber, no data leaving your machine. Same coding and logic tools for a kid in a remote province as for a developer in Sofia: building a website, learning to program, without hardware as a barrier.
 
-**V0.1 is in development**, kept free and local for every Bulgarian.
 
-This repo hosts the **LoRA adapter** on [Qwen2.5-Coder-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-Coder-7B-Instruct), trained on thousands of Bulgarian coding examples (OPUS-translated, no prompt poisoning). Use it as the coding model that speaks Bulgarian first. A lightweight, 4GB-friendly SLM variant is planned for offline use.
+## Model Details
 
-## Usage
+### Model Description
 
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
-from peft import PeftModel
-import torch
+<!-- Provide a longer summary of what this model is. -->
 
-base = "Qwen/Qwen2.5-Coder-7B-Instruct"
-adapter = "kyleparrratt/Vitosha-GPT-Code"
 
-tokenizer = AutoTokenizer.from_pretrained(base, trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained(
-    base,
-    torch_dtype=torch.bfloat16,
-    device_map="auto",
-)
-model = PeftModel.from_pretrained(model, adapter, is_trainable=False)
 
-messages = [
-    {"role": "system", "content": "Ти си полезен асистент за програмиране. Отговаряш на български."},
-    {"role": "user", "content": "Напиши функция на Python за проверка на просто число и обясни на български."},
-]
-text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
-inputs = tokenizer(text, return_tensors="pt").to(model.device)
-out = model.generate(**inputs, max_new_tokens=512, do_sample=False, pad_token_id=tokenizer.eos_token_id)
-print(tokenizer.decode(out[0][inputs.input_ids.shape[1]:], skip_special_tokens=True))
-```
+- **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]
 
-## Training
+### Model Sources [optional]
 
-- **Base:** Qwen2.5-Coder-7B-Instruct  
-- **Data:** Bulgarian coding data from evol-codealpaca-v1: prompts and completions translated to Bulgarian with OPUS (opus-mt-tc-big-en-bg), 100% Bulgarian-target examples, no boost phrase  
-- **Adapter:** LoRA r=16, trained with Unsloth  
-- **Inference:** Use `transformers` + PEFT (not Unsloth inference, to avoid RoPE issues)
+<!-- Provide the basic links for the model. -->
 
-## Limitations
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
 
-- Occasional English in explanations. Including “Отговори на български.” in the user message keeps output in Bulgarian.  
-- Code identifiers and APIs stay in English; explanations and prose are in Bulgarian.
+## Uses
 
-## License
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
 
-MIT. Adapter and card as-is; base model terms apply.
+### 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]
+### Framework versions
+
+- PEFT 0.18.1