Text Generation
Transformers
Safetensors
glm_moe_dsa
nvidia
nvfp4
quantized
Mixture of Experts
modelopt
glm
8-bit precision
Instructions to use CortexLM/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use CortexLM/test with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="CortexLM/test")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("CortexLM/test") model = AutoModelForCausalLM.from_pretrained("CortexLM/test") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use CortexLM/test with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "CortexLM/test" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CortexLM/test", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/CortexLM/test
- SGLang
How to use CortexLM/test with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "CortexLM/test" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CortexLM/test", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "CortexLM/test" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "CortexLM/test", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use CortexLM/test with Docker Model Runner:
docker model run hf.co/CortexLM/test
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| "model_type": "glm_moe_dsa", | |
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| "n_routed_experts": 256, | |
| "n_shared_experts": 1, | |
| "norm_topk_prob": true, | |
| "num_attention_heads": 64, | |
| "num_experts_per_tok": 8, | |
| "num_hidden_layers": 78, | |
| "num_key_value_heads": 64, | |
| "num_nextn_predict_layers": 1, | |
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| "qk_nope_head_dim": 192, | |
| "qk_rope_head_dim": 64, | |
| "rms_norm_eps": 1e-05, | |
| "rope_interleave": true, | |
| "rope_parameters": { | |
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| "rope_type": "default" | |
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| "scoring_func": "sigmoid", | |
| "tie_word_embeddings": false, | |
| "topk_group": 1, | |
| "topk_method": "noaux_tc", | |
| "transformers_version": "5.5.0", | |
| "use_cache": true, | |
| "v_head_dim": 256, | |
| "vocab_size": 154880, | |
| "quantization_config": { | |
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