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base_model: unsloth/Qwen2.5-7B-Instruct
tags:
- text-generation-inference
- transformers
- unsloth
- qwen2
- trl
- instruction-tuned
- supervised-finetuning
- causal-lm
license: apache-2.0
language:
- en
pipeline_tag: text-generation
---
# Uploaded Model
- **Developed by:** Harsha901
- **License:** Apache-2.0
- **Finetuned from model:** unsloth/Qwen2.5-7B-Instruct
This Qwen2.5-7B model was fine-tuned using **Unsloth** for faster and more memory-efficient training, together with Hugging Face’s **TRL** library for supervised fine-tuning.
[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)
---
## Model Overview
This is an **instruction-tuned causal language model** based on **Qwen2.5-7B**, designed to follow user prompts accurately and generate coherent, high-quality responses.
The model preserves the general-purpose strengths of Qwen2.5 while benefiting from domain-focused supervised fine-tuning.
---
## Training Details
- **Base model:** Qwen2.5-7B-Instruct (Unsloth variant)
- **Fine-tuning method:** Supervised Fine-Tuning (SFT)
- **Frameworks:** Hugging Face Transformers + TRL
- **Acceleration:** Unsloth (2× faster training, reduced VRAM usage)
- **Precision:** FP16 / BF16 (hardware dependent)
---
## Usage
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "Harsha901/<YOUR-MODEL-NAME>"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id,
device_map="auto",
torch_dtype="auto"
)
````
---
## Limitations
* Outputs may contain factual or reasoning errors
* Not intended for high-stakes or safety-critical applications
* Performance depends on prompt quality and context length
---
## License
Released under the **Apache 2.0 License**, consistent with the base Qwen2.5 model.
---
## Acknowledgements
* **Qwen Team** for the Qwen2.5 base model
* **Unsloth** for efficient fine-tuning optimizations
* **Hugging Face** for the training and hosting ecosystem
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