Reinforcement Learning
Transformers
Safetensors
qwen3
text-generation
sdpo
srpo
ema
text-generation-inference
Instructions to use SeongryongJung/qwen3-4b-chemistry-srpo-ema005 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SeongryongJung/qwen3-4b-chemistry-srpo-ema005 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("SeongryongJung/qwen3-4b-chemistry-srpo-ema005") model = AutoModelForCausalLM.from_pretrained("SeongryongJung/qwen3-4b-chemistry-srpo-ema005", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model-00001-of-00002.safetensors from SeongryongJung/qwen3-4b-chemistry-srpo-ema005: direct link, hf CLI and curl.
- Browser
- Download file 4.99 GB
-
https://huggingface.co/SeongryongJung/qwen3-4b-chemistry-srpo-ema005/resolve/main/model-00001-of-00002.safetensors
- Command line
-
hf download hf://SeongryongJung/qwen3-4b-chemistry-srpo-ema005/model-00001-of-00002.safetensors
-
curl -L -o model-00001-of-00002.safetensors https://huggingface.co/SeongryongJung/qwen3-4b-chemistry-srpo-ema005/resolve/main/model-00001-of-00002.safetensors
4.99 GB
- Xet hash:
- 3df87fd8ea93ff921d12571164ced1dfa642f02cc569985c0fe3eeff469f8736
- Size of remote file:
- 4.99 GB
- SHA256:
- e5a5f8d034fed5027fa963acd1886cbd250f6bc5463c481cbf262e23e2e0a10d
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