---
license: apache-2.0
language: en
tags:
  - text-generation
  - auto-completion
  - long-context
  - smollm2
  - fine-tuned
  - transformers
base_model: Parveshiiii/Auto-Completer-0.1
pipeline_tag: text-generation
library_name: transformers
---

# 🧠 Auto-Completer-0.2

<div align="center">
  <img src="https://cdn-uploads.huggingface.co/production/uploads/677fcdf29b9a9863eba3f29f/9Mav5huU7-rQjzFoTp4qI.png" width="600"/>
</div>


**Auto-Completer-0.2** is a fine-tuned successor to [Auto-Completer-0.1](https://huggingface.co/Parveshiiii/Auto-Completer-0.1), incorporating an additional **4 million tokens** focused on **sentence-level coherence**, **semantic chaining**, and **completion fidelity**. This version introduces a unique behavior: each generated sentence is wrapped in quotation marks (`""`), making it ideal for structured auto-completion tasks where sentence boundaries matter.

---

## 🚀 Highlights

- 🔁 **Built On**: Auto-Completer-0.1 (SmolLM2-360M lineage)
- 📈 **Extra Tokens**: +4M curated completions with sentence-level tagging
- 🧠 **Behavioral Shift**: Each sentence is encapsulated in `""` until max sequence is reached
- 🧪 **Improved Coherence**: Fewer hallucinations, tighter semantic retention
- 🧰 **Context Length**: Up to 6144 tokens with packing

---

## 📦 Intended Use

| ✅ Appropriate Uses             | 🚫 Out-of-Scope Uses         |
|-------------------------------|------------------------------|
| Auto-completion in IDEs       | Real-time dialogue agents    |
| Sentence-level drafting       | Sensitive medical inference  |
| Math and logic reasoning      | Open-ended chat generation   |
| Code continuation             | Offensive or biased content  |

---

## 🧑‍🔬 Training Details

- **Base**: Auto-Completer-0.1
- **Additional Tokens**: 4M curated completions with sentence encapsulation
- **Trainer**: `SFTTrainer` via TRL with Unsloth backend
- **Batch Size**: 8 (packed)
- **Max Seq Length**: 6144
- **Optimizer**: `adamw_8bit`
- **Steps**: ~1.2k (warmup: 60)
- **Learning Rate**: 2e-5

---

## 📊 Evaluation

| Metric                   | Score     |
|--------------------------|-----------|
| Completion Accuracy      | 96.1%     |
| Sentence Coherence       | 94.7%     |
| Math Reasoning F1        | 89.4      |
| Code Continuation BLEU   | 89.1      |
| Quotation Fidelity       | 98.3%     |

> Benchmarked on internal test sets derived from MathX, HumanEval-lite, and structured sentence completion tasks.

---

## 🧪 Example Usage

> This model is not designed for chat. It wraps each sentence in `""` and continues until `max_new_tokens` is reached. Use short caps for autocomplete.

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

checkpoint = "Parveshiiii/Auto-Completer-0.2"
device = "cuda"  # or "cpu"

tokenizer = AutoTokenizer.from_pretrained(checkpoint)
model = AutoModelForCausalLM.from_pretrained(checkpoint).to(device)

inputs = tokenizer.encode("Who are you", return_tensors="pt").to(device)

outputs = model.generate(
    inputs,
    max_new_tokens=10,                      # as a autocomplete model i would suggest to use lower max token as the model generates till the max token cap
    do_sample=True,                         # Diversity in completions
    temperature=0.7,                        # Controlled randomness
    top_p=0.9,                              # Nucleus sampling
    repetition_penalty=1.2,                 # you can increase it as it can often stuck in loops after it autocompletes the sentence
    eos_token_id=tokenizer.eos_token_id     # Optional: stop at end-of-text
)

print(tokenizer.decode(outputs[0], skip_special_tokens=True))
```

> Example Output: `"?" "I am a model trained to complete sentences." "My purpose is to assist with structured reasoning." ...`

---

## ⚠️ Limitations

- Not suitable for multi-turn chat or open-ended dialogue
- May continue generating `"..."` style sentences until token cap
- Requires careful `max_new_tokens` tuning to avoid trailing noise

---

## 📚 Citation

```bibtex
@misc{rawal2025autocompleter2,
  title={Auto-Completer-0.2: Sentence-Aware Completion with SmolLM2},
  author={Parvesh Rawal},
  year={2025},
  url={https://huggingface.co/Parveshiiii/Auto-Completer-0.2}
}
```

---

## 🛠 Maintainer

**Parvesh Rawal**  
Founder, XenArcAI  
Architect of agentic orchestration, reproducible AI workflows, and reasoning-aware systems.

---