Text Generation
MLX
Safetensors
English
qwen3_5_moe
reasoning
distillation
chain-of-thought
qwen
qwen3.6
mixture-of-experts
Mixture of Experts
lora
unsloth
abliterated
uncensored
conversational
Instructions to use deadbydawn101/RavenX-Sec-35B-Security-RATH-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use deadbydawn101/RavenX-Sec-35B-Security-RATH-mlx with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("deadbydawn101/RavenX-Sec-35B-Security-RATH-mlx") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Unsloth Studio
How to use deadbydawn101/RavenX-Sec-35B-Security-RATH-mlx with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for deadbydawn101/RavenX-Sec-35B-Security-RATH-mlx to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for deadbydawn101/RavenX-Sec-35B-Security-RATH-mlx to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for deadbydawn101/RavenX-Sec-35B-Security-RATH-mlx to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="deadbydawn101/RavenX-Sec-35B-Security-RATH-mlx", max_seq_length=2048, ) - Pi
How to use deadbydawn101/RavenX-Sec-35B-Security-RATH-mlx with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "deadbydawn101/RavenX-Sec-35B-Security-RATH-mlx"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "deadbydawn101/RavenX-Sec-35B-Security-RATH-mlx" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use deadbydawn101/RavenX-Sec-35B-Security-RATH-mlx with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "deadbydawn101/RavenX-Sec-35B-Security-RATH-mlx"
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default deadbydawn101/RavenX-Sec-35B-Security-RATH-mlx
Run Hermes
hermes
- MLX LM
How to use deadbydawn101/RavenX-Sec-35B-Security-RATH-mlx with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "deadbydawn101/RavenX-Sec-35B-Security-RATH-mlx"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "deadbydawn101/RavenX-Sec-35B-Security-RATH-mlx" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "deadbydawn101/RavenX-Sec-35B-Security-RATH-mlx", "messages": [ {"role": "user", "content": "Hello"} ] }'
v5.0: config.json — 35B MoE, 680K, 6-step RATH
Browse files- config.json +109 -0
config.json
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{
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"architectures": [
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"Qwen3_5MoeForConditionalGeneration"
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],
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"bos_token_id": null,
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"eos_token_id": 248046,
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"image_token_id": 248056,
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"model_name": "unsloth/Qwen3.6-35B-A3B",
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"model_type": "qwen3_5_moe",
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"pad_token_id": 248055,
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"text_config": {
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"attention_bias": false,
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"attention_dropout": 0.0,
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"attn_output_gate": true,
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"bos_token_id": 248044,
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"torch_dtype": "bfloat16",
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"eos_token_id": 248044,
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"full_attention_interval": 4,
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"head_dim": 256,
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"hidden_act": "silu",
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"hidden_size": 2048,
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"initializer_range": 0.02,
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"layer_types": [
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"linear_attention",
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"linear_attention",
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"linear_attention",
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"full_attention",
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"linear_attention",
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"linear_attention",
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"linear_attention",
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"full_attention",
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"linear_attention",
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"linear_attention",
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"linear_attention",
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"full_attention",
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"linear_attention",
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"linear_attention",
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"linear_attention",
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"full_attention",
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"linear_attention",
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"linear_attention",
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"linear_attention",
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"full_attention",
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"linear_attention",
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"linear_attention",
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"linear_attention",
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"full_attention",
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"linear_attention",
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"linear_attention",
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"linear_attention",
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"full_attention",
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"linear_attention",
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"linear_attention",
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"linear_attention",
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"full_attention",
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"linear_attention",
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"linear_attention",
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"linear_attention",
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"full_attention",
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"linear_attention",
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"linear_attention",
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"linear_attention",
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"full_attention"
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],
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"linear_conv_kernel_dim": 4,
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"linear_key_head_dim": 128,
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"linear_num_key_heads": 16,
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"linear_num_value_heads": 32,
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"linear_value_head_dim": 128,
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"mamba_ssm_dtype": "float32",
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"max_position_embeddings": 262144,
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"model_type": "qwen3_5_moe_text",
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"moe_intermediate_size": 512,
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"mtp_num_hidden_layers": 1,
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"mtp_use_dedicated_embeddings": false,
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"num_attention_heads": 16,
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"num_experts": 256,
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"num_experts_per_tok": 8,
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"num_hidden_layers": 40,
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"num_key_value_heads": 2,
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"output_router_logits": false,
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"pad_token_id": null,
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"partial_rotary_factor": 0.25,
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"rms_norm_eps": 1e-06,
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"rope_parameters": {
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"mrope_interleaved": true,
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"mrope_section": [
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11,
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11,
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10
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],
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"partial_rotary_factor": 0.25,
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"rope_theta": 10000000,
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"type": "default"
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},
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"router_aux_loss_coef": 0.001,
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"shared_expert_intermediate_size": 512,
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"tie_word_embeddings": false,
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"use_cache": true,
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"vocab_size": 248320
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},
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"unsloth_version": "2026.4.1",
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"use_cache": false,
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"video_token_id": 248057,
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"vision_end_token_id": 248054,
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"vision_start_token_id": 248053
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}
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