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anmoldhandhania93
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Model Details
Model Provider
anmoldhandhania93
Model Tree
unsloth/Qwen2.5-3B-Instruct-bnb-4bit
Input Modalities
Output Modalities
Supported Functionality
ANMOLGPT-3B-v0.1 is an instruction-following language model built by fine-tuning Qwen2.5-3B-Instruct using QLoRA with Unsloth Studio.
This release serves as the foundation of the ANMOLGPT project and demonstrates the complete workflow of dataset preparation, fine-tuning, evaluation, and deployment.
Although this is an early preview release, it establishes the baseline for future versions that will include larger datasets, stronger reasoning capabilities, and extensive benchmarking.
| Parameter | Value |
|---|---|
| LoRA Rank | 8 |
| LoRA Alpha | 16 |
| LoRA Dropout | 0.05 |
| Context Length | 1024 |
| Learning Rate | 1e-4 |
| Batch Size | 2 |
| Gradient Accumulation | 8 |
| Effective Batch Size | 16 |
| Max Steps | 100 |
| Precision | 4-bit QLoRA |
Evaluated using the EleutherAI LM Evaluation Harness.
| Benchmark | Metric | Score |
|---|---|---|
| HellaSwag | Accuracy | 54.29% |
| HellaSwag | Normalized Accuracy | 73.21% |
| PIQA | Accuracy | 77.97% |
| PIQA | Normalized Accuracy | 78.40% |
| ARC-Easy | Accuracy | 77.95% |
| ARC-Easy | Normalized Accuracy |
| Domain | Accuracy |
|---|---|
| Social Sciences | 76.86% |
| Other | 71.00% |
| STEM | 61.37% |
| Humanities | 57.47% |
These results represent the baseline performance of ANMOLGPT-3B-v0.1 and will be expanded in future releases.
python
from transformers import AutoTokenizer, AutoModelForCausalLMmodel_name = "anmoldhandhania93/ANMOLGPT-3B-v0.1"tokenizer = AutoTokenizer.from_pretrained(model_name)model = AutoModelForCausalLM.from_pretrained(model_name)prompt = "Explain reinforcement learning."inputs = tokenizer(prompt, return_tensors="pt")outputs = model.generate(**inputs,max_new_tokens=200)print(tokenizer.decode(outputs[0], skip_special_tokens=True))
ANMOLGPT is suitable for:
This is an early proof-of-concept release.
Current limitations include:
bibtex
@misc{anmolgpt2026,title={ANMOLGPT-3B-v0.1},author={Anmol Dhandhania},year={2026},publisher={Hugging Face},url={https://huggingface.co/anmoldhandhania93/ANMOLGPT-3B-v0.1}}
ANMOLGPT was built using:
Future versions of ANMOLGPT will focus on:
Feedback, issues, and contributions are welcome.
| 75.29% |
| Winogrande | Accuracy | 70.24% |
| TruthfulQA (MC2) | Accuracy | 42.52% |
| MMLU | Accuracy | 65.59% |