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
Update model weights
Browse files- config.json +34 -0
- model.safetensors +3 -0
config.json
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{
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"architectures": [
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"MamLAForCausalLM"
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],
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"bos_token_id": 1,
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"d_model": 2048,
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"dtype": "float32",
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"eos_token_id": 2,
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"mamba_d_conv": 4,
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"mamba_d_state": 64,
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"mamba_expand": 2,
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"mamba_layers_per_cycle": 7,
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"mamba_n_heads": 16,
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"mla_kv_lora_rank": 128,
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"mla_layers_per_cycle": 1,
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"mla_n_heads": 16,
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"mla_q_lora_rank": 128,
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"mla_qk_nope_head_dim": 32,
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"mla_qk_rope_head_dim": 32,
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"mla_v_head_dim": 32,
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"model_type": "mamla",
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"moe_d_ff": 1024,
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"moe_num_experts": 4,
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"moe_top_k": 2,
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"n_layer": 24,
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"num_experts": 4,
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"num_experts_per_tok": 2,
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"num_layers": 16,
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"pad_token_id": 0,
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"pad_vocab_size_multiple": 8,
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"tie_word_embeddings": true,
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"transformers_version": "5.0.0",
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"vocab_size": 32000
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}
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:41a4536def960e98b77a5818b2ca97b5e19b506c4aced51389a887c320f106bd
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size 3602406968
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