Shlok307
/

ai_interview-lora

@@ -10,200 +10,81 @@ tags:
 - trl
 ---
-# Model Card for Model ID
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-### Framework versions
-- PEFT 0.18.0

 - trl
 ---
+#  Gemma 3 Interview LoRA — 1B Instruct
+This model is a **QLoRA fine-tuned version** of **Gemma-3-1B-IT**, trained on a curated dataset of **5,002 interview-style Q&A samples** across:
+- **Artificial Intelligence (AI)**
+- **General Programming**
+- **Web Development**
+The goal is to enhance Gemma-3 into a **technical interview assistant**, capable of:
+- Generating domain-specific interview questions
+- Providing accurate, structured, exam-style answers
+- Explaining concepts clearly and concisely
+- Maintaining a professional and consistent interview tone
+---
+##  Dataset
+The model was fine-tuned on a dataset containing 5,002 samples with the fields:
+| Field | Description |
+|-------|-------------|
+| **domain** | AI, General Programming, Web Development |
+| **question** | Interview question from that domain |
+| **answer** | Ground-truth, explanation-style answer |
+Each training row was converted into:
+- Instruction:
+  `"Answer this <domain> interview question: <question>"`
+- Response:
+  `"<answer>"`
+---
+##  Usage Example
+### Python
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+model_id = "Shlok307/gemma3-interview-lora"
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    device_map="auto",
+    torch_dtype=torch.float16
+)
+prompt = [
+    {"role": "user", "content": "Answer this AI interview question: What is backpropagation?"}
+]
+input_ids = tokenizer.apply_chat_template(
+    prompt,
+    tokenize=True,
+    add_generation_prompt=True,
+    return_tensors="pt"
+).to(model.device)
+output = model.generate(
+    input_ids,
+    max_new_tokens=200,
+    do_sample=True,
+    temperature=0.7
+)
+print(tokenizer.decode(output[0], skip_special_tokens=True))
+```
+## Citation
+```
+@model{gemma3_interview_lora,
+  title={Gemma 3 Interview LoRA — 1B IT},
+  author={Shlok Talhar},
+  year={2025},
+  url={https://huggingface.co/Shlok307/gemma3-interview-lora}
+}
+```