---
library_name: transformers
pipeline_tag: text-generation
tags:
  - aethersearch
  - agentic-rl
  - search-augmented-generation
  - qwen2
  - sft
  - dpo
  - reinforcement-learning
language:
  - en
---

# AetherSearch

AetherSearch is a search-augmented language model release trained through a
multi-stage post-training pipeline with SFT, DPO, and reinforcement learning.

The released weights are provided in Hugging Face Transformers format and can be
loaded with `AutoModelForCausalLM` and `AutoTokenizer`.

## Files

- `model.safetensors`: model weights.
- `config.json` and `generation_config.json`: Transformers configuration.
- `tokenizer.json`, `tokenizer_config.json`, `vocab.json`, `merges.txt`,
  `added_tokens.json`, and `special_tokens_map.json`: tokenizer assets.
- `MODEL_MANIFEST.sha256`: SHA256 checksums for the uploaded files.

## Usage

```python
from transformers import AutoModelForCausalLM, AutoTokenizer

repo_id = "muradil211/AetherSearch"

tokenizer = AutoTokenizer.from_pretrained(repo_id)
model = AutoModelForCausalLM.from_pretrained(
    repo_id,
    torch_dtype="auto",
    device_map="auto",
)
```

## Notes

The companion training code is released at:
https://github.com/Muradil-mamat-211/AetherSearch

License and upstream base-model attribution should be set according to the
actual base model and data release terms before wider redistribution.