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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.
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