create model card lloro sql (#1)

- create model card lloro sql (9e3d4b7931bdb51bd98773fb9c2b9f9b810f8308)


Co-authored-by: Alves <[email protected]>

README.md

@@ -0,0 +1,130 @@
+---
+library_name: transformers
+base_model: meta-llama/Meta-Llama-3-8B-Instruct
+license: apache-2.0
+language:
+- pt
+tags:
+- code
+- sql
+- finetuned
+- portugues-BR
+---
+**Lloro SQL**
+
+<img src="https://cdn-uploads.huggingface.co/production/uploads/653176dc69fffcfe1543860a/h0kNd9OTEu1QdGNjHKXoq.png" width="300" alt="Lloro-7b Logo"/>
+
+
+Lloro SQL, developed by Semantix Research Labs, is a language Model that was trained to effectively transform Portuguese queries into SQL Code. It is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct,  that was trained on Bird and Spider public datasets.  The fine-tuning process was performed using the QLORA metodology on a GPU A100 with 40 GB of RAM.
+
+ 
+
+**Model description**
+
+
+Model type: A 7B parameter  fine-tuned on GretelAI public datasets.
+
+Language(s) (NLP): Primarily Portuguese, but the model is capable to understand English as well
+
+Finetuned from model: meta-llama/Meta-Llama-3-8B-Instruct
+
+ 
+
+**What is Lloro's intended use(s)?**
+
+
+Lloro is built for Text2SQL in Portuguese contexts .
+
+Input : Text
+
+Output : Text (Code)
+
+
+**Usage**
+
+
+Using an OpenAI compatible inference server (like [vLLM](https://docs.vllm.ai/en/latest/index.html))
+
+```python
+from openai import OpenAI
+client = OpenAI(
+    api_key="EMPTY",
+    base_url="http://localhost:8000/v1",
+)
+def generate_responses(instruction, client=client):
+    
+    chat_response = client.chat.completions.create(
+    model=<model>,
+    messages=[
+        {"role": "system", "content": "Você escreve a instrução SQL que responde às perguntas feitas. Você NÃO FORNECE NENHUM COMENTÁRIO OU EXPLICAÇÃO sobre o que o código faz, apenas a instrução SQL terminando em ponto e vírgula. Você utiliza todos os comandos disponíveis na especificação SQL, como: [SELECT, WHERE, ORDER, LIMIT, CAST, AS, JOIN]."},
+        {"role": "user", "content": instruction},
+    ]
+)
+    
+    return chat_response.choices[0].message.content
+
+output = generate_responses(user_prompt)
+
+```
+ 
+
+
+**Params**
+Training Parameters
+| Params                           | Training Data                   | Examples                        | Tokens     | LR     |
+|----------------------------------|---------------------------------|---------------------------------|------------|--------|
+| 8B                               | GretelAI public datasets        | 65000                           | 18.000.000 | 9e-5   |
+ 
+
+**Model Sources**
+
+GretelAI: https://huggingface.co/datasets/gretelai/synthetic_text_to_sql
+
+ 
+
+**Performance**
+| Modelo         | LLM as Judge | Code Bleu Score | Rouge-L |  CodeBert- Precision | CodeBert-Recall | CodeBert-F1 | CodeBert-F3 |
+|----------------|--------------|-----------------|---------|----------------------|-----------------|-------------|-------------|
+| Llama 3 - Base | 65.48%       | 0.4583          | 0.6361  |  0.8815              | 0.8871          | 0.8835      | 0.8862      |
+| Llama 3 - FT   | 62.57%       | 0.6512          | 0.7965  |  0.9458              | 0.9469          | 0.9459      | 0.9466      |
+
+
+**Training Infos:**
+The following hyperparameters were used during training:
+
+| Parameter                 | Value                |
+|---------------------------|----------------------|
+| learning_rate             | 9e-5                 |
+| weight_decay              | 0.001               |
+| train_batch_size          | 16                    |
+| eval_batch_size           | 8                   |
+| seed                      | 42                   |
+| optimizer                 | Adam - adamw_8bit |
+| lr_scheduler_type         | cosine               |
+| num_epochs                | 3.0                  |
+
+**QLoRA hyperparameters**
+The following parameters related with the Quantized Low-Rank Adaptation and Quantization were used during training:
+
+| Parameter       | Value   |
+|-----------------|---------|
+| lora_r          | 16      |
+| lora_alpha      | 64      |
+| lora_dropout    | 0       |
+
+
+
+**Framework versions**
+| Library       | Version   |
+|---------------|-----------|
+| accelerate    | 0.21.0    |
+| bitsandbytes  | 0.42.0    |
+| Datasets      | 2.14.3    |
+| peft          | 0.4.0     |
+| Pytorch       | 2.0.1     |
+| safetensors   | 0.4.1     |
+| scikit-image  | 0.22.0    |
+| scikit-learn  | 1.3.2     |
+| Tokenizers    | 0.14.1    |
+| Transformers  | 4.37.2    |
+| trl           | 0.4.7     |