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-00002-of-00002.safetensors from SeongryongJung/qwen3-4b-chemistry-srpo-ema005: direct link, hf CLI and curl.
- Browser
- Download file 3.83 GB
-
https://huggingface.co/SeongryongJung/qwen3-4b-chemistry-srpo-ema005/resolve/main/model-00002-of-00002.safetensors
- Command line
-
hf download hf://SeongryongJung/qwen3-4b-chemistry-srpo-ema005/model-00002-of-00002.safetensors
-
curl -L -o model-00002-of-00002.safetensors https://huggingface.co/SeongryongJung/qwen3-4b-chemistry-srpo-ema005/resolve/main/model-00002-of-00002.safetensors
3.83 GB
- Xet hash:
- c844a4b5de620151df7db6ea26cd17318708f77ef21ff607fdc602af57598d66
- Size of remote file:
- 3.83 GB
- SHA256:
- 200cf391c6ea77e1abbd84bcd6aab739b460226986e3a0381b77b89b8a8aea75
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