Instructions to use EvoNet/EvoNet-AI-V1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use EvoNet/EvoNet-AI-V1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="EvoNet/EvoNet-AI-V1")# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("EvoNet/EvoNet-AI-V1", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use EvoNet/EvoNet-AI-V1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "EvoNet/EvoNet-AI-V1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "EvoNet/EvoNet-AI-V1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/EvoNet/EvoNet-AI-V1
- SGLang
How to use EvoNet/EvoNet-AI-V1 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 "EvoNet/EvoNet-AI-V1" \ --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": "EvoNet/EvoNet-AI-V1", "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 "EvoNet/EvoNet-AI-V1" \ --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": "EvoNet/EvoNet-AI-V1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use EvoNet/EvoNet-AI-V1 with Docker Model Runner:
docker model run hf.co/EvoNet/EvoNet-AI-V1
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d8d873c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 | {
"architectures": [
"MamLAForCausalLM"
],
"bos_token_id": 1,
"d_model": 2048,
"dtype": "float32",
"eos_token_id": 2,
"mamba_d_conv": 4,
"mamba_d_state": 64,
"mamba_expand": 2,
"mamba_layers_per_cycle": 7,
"mamba_n_heads": 16,
"mla_kv_lora_rank": 128,
"mla_layers_per_cycle": 1,
"mla_n_heads": 16,
"mla_q_lora_rank": 128,
"mla_qk_nope_head_dim": 32,
"mla_qk_rope_head_dim": 32,
"mla_v_head_dim": 32,
"model_type": "mamla",
"moe_d_ff": 1024,
"moe_num_experts": 4,
"moe_top_k": 2,
"n_layer": 24,
"num_experts": 4,
"num_experts_per_tok": 2,
"num_layers": 16,
"pad_token_id": 0,
"pad_vocab_size_multiple": 8,
"tie_word_embeddings": true,
"transformers_version": "5.0.0",
"vocab_size": 32000
}
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