Text Generation
Transformers
PyTorch
English
maba_sparse
maba
maba-v1.5
maba-v1.5-exp
architecture
recurrent
decoupled-gated-delta-attention
dgda
linear-attention
linear-recurrence
sparse-attention
maba-sa
mla
multi-head-latent-attention
nope
dg-indexer
centroid-indexing
hca
3-stream
swiglu
rmsnorm
speculative-decoding
mtp
multi-token-prediction
scaling
100m
1b
3b
7b
30b
Instructions to use AndrewThompson1233/maba-v1.5-exp-architecture with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AndrewThompson1233/maba-v1.5-exp-architecture with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="AndrewThompson1233/maba-v1.5-exp-architecture")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("AndrewThompson1233/maba-v1.5-exp-architecture", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use AndrewThompson1233/maba-v1.5-exp-architecture with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AndrewThompson1233/maba-v1.5-exp-architecture" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "AndrewThompson1233/maba-v1.5-exp-architecture", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/AndrewThompson1233/maba-v1.5-exp-architecture
- SGLang
How to use AndrewThompson1233/maba-v1.5-exp-architecture 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 "AndrewThompson1233/maba-v1.5-exp-architecture" \ --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": "AndrewThompson1233/maba-v1.5-exp-architecture", "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 "AndrewThompson1233/maba-v1.5-exp-architecture" \ --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": "AndrewThompson1233/maba-v1.5-exp-architecture", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use AndrewThompson1233/maba-v1.5-exp-architecture with Docker Model Runner:
docker model run hf.co/AndrewThompson1233/maba-v1.5-exp-architecture
Ctrl+K