Reinforcement Learning
Transformers
Safetensors
English
gpt_oss
text-generation
optimization
operations-research
milp
gurobi
Instructions to use microsoft/OptiMind-RL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/OptiMind-RL with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("microsoft/OptiMind-RL") model = AutoModelForCausalLM.from_pretrained("microsoft/OptiMind-RL", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from microsoft/OptiMind-RL: direct link, hf CLI and curl.
- Browser
- Download file 27.9 MB
-
https://huggingface.co/microsoft/OptiMind-RL/resolve/main/tokenizer.json
- Command line
-
hf download hf://microsoft/OptiMind-RL/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/microsoft/OptiMind-RL/resolve/main/tokenizer.json
27.9 MB
- Xet hash:
- 59f22360b51bf1a137fb80e14df310b4b249bed6cc64565aa0c401ca19ffcd04
- Size of remote file:
- 27.9 MB
- SHA256:
- 0614fe83cadab421296e664e1f48f4261fa8fef6e03e63bb75c20f38e37d07d3
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