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Model: vivekmdrift/maya-qwen-7b
Source: Original Platform

README.md

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+---
+license: apache-2.0
+base_model: Qwen/Qwen2.5-7B-Instruct
+tags:
+  - fine-tuned
+  - qwen2.5
+  - customer-support
+  - unsloth
+  - lora
+pipeline_tag: text-generation
+---
+
+# maya-qwen-7b
+
+Fine-tuned version of [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct)
+for customer support conversations.
+
+## Training Details
+
+- **Method**: LoRA fine-tuning with Unsloth + TRL SFTTrainer
+- **Base model**: Qwen/Qwen2.5-7B-Instruct
+- **LoRA rank**: 16
+- **Format**: ChatML
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("vivekmdrift/maya-qwen-7b")
+tokenizer = AutoTokenizer.from_pretrained("vivekmdrift/maya-qwen-7b")
+
+messages = [
+    {"role": "system", "content": "You are a helpful customer support agent."},
+    {"role": "user", "content": "How can I track my order?"},
+]
+
+text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+inputs = tokenizer(text, return_tensors="pt")
+outputs = model.generate(**inputs, max_new_tokens=256)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```