Text Generation
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maba_sparse
maba
maba-v2
maba-v2-architecture
architecture
recurrent
dgda
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maba-sa
mla
multi-head-latent-attention
deepseek
qwen
minicpm
mamba
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transformer
causal-lm
llm
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multi-token-prediction
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scaling
100m
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30b
Instructions to use AndrewThompson1233/maba-v2-architecture with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AndrewThompson1233/maba-v2-architecture with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="AndrewThompson1233/maba-v2-architecture")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("AndrewThompson1233/maba-v2-architecture", device_map="auto") - RWKV
How to use AndrewThompson1233/maba-v2-architecture with RWKV:
# No code snippets available yet for this library. # To use this model, check the repository files and the library's documentation. # Want to help? PRs adding snippets are welcome at: # https://github.com/huggingface/huggingface.js
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use AndrewThompson1233/maba-v2-architecture with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "AndrewThompson1233/maba-v2-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-v2-architecture", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/AndrewThompson1233/maba-v2-architecture
- SGLang
How to use AndrewThompson1233/maba-v2-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-v2-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-v2-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-v2-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-v2-architecture", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use AndrewThompson1233/maba-v2-architecture with Docker Model Runner:
docker model run hf.co/AndrewThompson1233/maba-v2-architecture
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