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 config.json from microsoft/OptiMind-RL: direct link, hf CLI and curl.
- Browser
- Download file 1.62 kB
-
https://huggingface.co/microsoft/OptiMind-RL/resolve/main/config.json
- Command line
-
hf download hf://microsoft/OptiMind-RL/config.json
-
curl -L -o config.json https://huggingface.co/microsoft/OptiMind-RL/resolve/main/config.json
1.62 kB
| { | |
| "architectures": [ | |
| "GptOssForCausalLM" | |
| ], | |
| "attention_bias": true, | |
| "attention_dropout": 0.0, | |
| "eos_token_id": 200002, | |
| "experts_per_token": 4, | |
| "head_dim": 64, | |
| "hidden_act": "silu", | |
| "hidden_size": 2880, | |
| "initial_context_length": 4096, | |
| "initializer_range": 0.02, | |
| "intermediate_size": 2880, | |
| "layer_types": [ | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "full_attention", | |
| "sliding_attention", | |
| "full_attention" | |
| ], | |
| "max_position_embeddings": 131072, | |
| "model_type": "gpt_oss", | |
| "num_attention_heads": 64, | |
| "num_experts_per_tok": 4, | |
| "num_hidden_layers": 24, | |
| "num_key_value_heads": 8, | |
| "num_local_experts": 32, | |
| "output_router_logits": false, | |
| "pad_token_id": 199999, | |
| "rms_norm_eps": 1e-05, | |
| "rope_scaling": { | |
| "beta_fast": 32.0, | |
| "beta_slow": 1.0, | |
| "factor": 32.0, | |
| "original_max_position_embeddings": 4096, | |
| "rope_type": "yarn", | |
| "truncate": false | |
| }, | |
| "rope_theta": 150000, | |
| "router_aux_loss_coef": 0.9, | |
| "sliding_window": 128, | |
| "swiglu_limit": 7.0, | |
| "tie_word_embeddings": false, | |
| "transformers_version": "4.55.0.dev0", | |
| "use_cache": true, | |
| "vocab_size": 201088, | |
| "torch_dtype": "bfloat16" | |
| } |