muradil211 / AetherSearch

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

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.