Instructions to use AndrewThompson1233/maba-v2-architecture with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

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
```

maba-v2-architecture / config.json

satana123fdfsaffsaf

commit26

a0ef70a 10 days ago

Raw History Blame Contribute Delete

832 Bytes

	{
	"architectures": [
	"MabaSparseForCausalLM"
	],
	"model_type": "maba_sparse",
	"vocab_size": 32768,
	"d_emb": 128,
	"dim": 640,
	"hidden_size": 640,
	"n_layers": 20,
	"num_hidden_layers": 20,
	"n_heads": 10,
	"num_attention_heads": 10,
	"d_head": 64,
	"d_k": 64,
	"d_v": 64,
	"d_c": 128,
	"d_idx": 64,
	"block_size": 64,
	"window_size": 128,
	"top_k": 32,
	"hca_pool_size": 64,
	"dist_lambda": 0.5,
	"kernel_size": 4,
	"conv_kernel_size": 4,
	"chunk_size": 16,
	"inversion_method": "adaptive",
	"inversion_threshold": 0.5,
	"adaptive_tol": 7e-05,
	"intermediate_size": 1248,
	"rms_norm_eps": 1e-06,
	"residual_gate_bias": 2.0,
	"mtp_depth": 2,
	"max_seq_len": 4096,
	"max_position_embeddings": 4096,
	"torch_dtype": "float32",
	"transformers_version": "4.49.0",
	"model_version": "1.5.0"
	}