Update README.md

README.md

@@ -1,202 +1,136 @@
 ---
 base_model: unsloth/Llama-3.2-1B-Instruct
 library_name: peft
+license: mit
+datasets:
+- gretelai/synthetic_text_to_sql
+language:
+- en
+pipeline_tag: text2text-generation
+tags:
+- SQL
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
+# Model Card for Llama3.2-SQL-1B
 
 
 ## Model Details
 
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
+This model is a fine-tuned version of Llama3.2-1B-Instruct, optimized for text-to-SQL generation tasks.
+It was trained on the **gretelai/synthetic_text_to_sql** dataset, which contains synthetic natural language questions and their corresponding SQL queries across a variety of domains.
 
+The model learns to:
+- Understand natural language instructions.
+- Generate syntactically correct and context-aware SQL queries.
+- Interpret structured schema information when included in the prompt.
 
+### Model Description
 
-- **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. -->
+- **Developed by:** Rustam Shiriyev
+- **Model type:** Instruction-tuned model on Text2SQL data
+- **Language(s) (NLP):** English
+- **License:** MIT
+- **Finetuned from model:** unsloth/Llama3.2-1B-Instruct
 
-- **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. -->
+- Natural Language to SQL translation
+- Educational or research applications
+- Lightweight inference for SQL query generation on small-scale tasks or apps
 
-[More Information Needed]
-
-### Downstream Use [optional]
+## Bias, Risks, and Limitations
 
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+- May not handle deeply nested or complex joins in SQL.
 
-[More Information Needed]
+## How to Get Started with the Model
 
-### Out-of-Scope Use
+```python
+from huggingface_hub import login
+from transformers import AutoTokenizer, AutoModelForCausalLM
+from peft import PeftModel
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+login(token="")  
 
-[More Information Needed]
+tokenizer = AutoTokenizer.from_pretrained("unsloth/Llama3.2-1B-Instruct",)
+base_model = AutoModelForCausalLM.from_pretrained(
+    "unsloth/Llama3.2-1B-Instruct",
+    device_map="auto", token=""
+)
 
-## Bias, Risks, and Limitations
+model = PeftModel.from_pretrained(base_model,"Rustamshry/Llama3.2-SQL-1B")
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
 
-[More Information Needed]
+question = "What are the vehicle safety testing organizations that operate in the UK and France?"
 
-### Recommendations
+context = 
+"""
+CREATE TABLE SafetyOrgs (name VARCHAR(20), country VARCHAR(10)); 
+INSERT INTO SafetyOrgs (name, country) VALUES ('Euro NCAP', 'UK'); 
+INSERT INTO SafetyOrgs (name, country) VALUES ('ADAC', 'Germany'); 
+INSERT INTO SafetyOrgs (name, country) VALUES ('UTAC', 'France');
+"""
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+instruction = (
+    "You are a skilled SQL assistant."
+    "Using the given database context, generate the correct SQL query to answer the question.\n\n"
+    f"Context: {context.strip()}"
+)
 
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+prompt = (
+    f"### Instruction:\n{instruction}\n\n"
+    f"### Question:\n{question}\n\n"
+    f"### Response:\n"
+)
 
-## How to Get Started with the Model
+input_ids = tokenizer(prompt, return_tensors="pt").to(model.device)
 
-Use the code below to get started with the model.
+outputs = model.generate(
+    **input_ids, 
+    max_new_tokens=2048
+)
 
-[More Information Needed]
+print(tokenizer.decode(outputs[0]),skip_special_tokens=True)
+```
 
 ## 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]
+-**Dataset**: gretelai/synthetic_text_to_sql which consists of 100,000 synthetic examples of natural language questions paired with corresponding SQL queries and explanations.
 
 ### 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]
+The model was fine-tuned using the Unsloth and LoRA. 
 
+-**LoRA rank**: 8
+-**Aplha**: 16
 
 #### 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 -->
+  -**batch size**:8, 
+  -**gradient accumulation steps**:4,
+  -**optimizer**:adamw_torch,
+  -**learning rate**:2e-5,
+  -**warmup_steps**:100,
+  -**fp16**:True,
+  -**epochs**:2,
+  -**weight_decay**:0.01,
+  -**lr_scheduler_type**:linear
 
 #### 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]
+- **Training time**: 8 hour
+- **Speed**: 0.22
 
 ### 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
+- Final Loss: 1.42 >> 0.48
 
-[More Information Needed]
 ### Framework versions
 
 - PEFT 0.14.0