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KirkAis
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KirkAis
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Lucent 5.0 is a 30 Billion parameter (32.5B dense) specialized coding and systems intelligence developed by KirkAI. Designed specifically for Minecraft client developers, mod authors, and protocol engineers, Lucent 5.0 transitions beyond simple code generation into empirical project-level engineering.
| Specification | Details |
|---|---|
| Model Scale | 30B / 32B Parameters (32.5 Billion Dense) |
| Base Architecture | Decoder-Only Transformer (Dense Causal LM) |
| Context Length | 32,768 – 131,072 tokens (Optimized for 8,192 training sequences) |
| Precision Options | Native BF16 / FP16, 4-bit QLoRA, GGUF (Q4_K_M, Q5_K_M, Q8_0) |
| Primary Ecosystems | Minecraft 1.8.9 (Forge MCP) & 1.20–1.21+ (Fabric / NeoForge Mojang) |
It possesses deep first-principles comprehension of:
Lucent 5.0 is trained to never silently guess or hallucinate runtime execution. Every technical implementation follows a rigorous scientific protocol:
text
TARGET ──► RECON ──► HYPOTHESES ──► DECISION ──► BUILD ──► TEST REPORT ──► SELF-AUDIT ──► KNOWLEDGE ΔVERIFIED: Proven by verified decompiled jar symbols, bytecode configs, or stated proofs.REASONED: Inferred through mathematical or logical deduction.UNVERIFIED: Compilations or runtime checks requiring local execution (./gradlew build).TODO, FIXME, and stubbed // ... comments; all code outputs are complete and production-ready.var\d+, aEg, wo(), vl()).| Component | Legacy Era (Forge) | Modern Era (Fabric / NeoForge) |
|---|---|---|
| Minecraft Versions | 1.8.9 (Kirk Architecture) | 1.20.x, 1.21.x, 1.21.11 (Ethane Architecture) |
| Mappings | MCP / Searge (EntityPlayerSP, C03PacketPlayer) | Mojang Mappings (LocalPlayer, ServerboundMovePlayerPacket) & Yarn |
| Java Runtimes | Java 8 | Java 21+ |
| Injection | Forge CoreMods, @SubscribeEvent, Sponge Mixin | Fabric Mixins (@Inject, @Redirect), Fabric Access Wideners |
| Rendering | GlStateManager, Tessellator, WorldRenderer | DrawContext, RenderSystem, BufferBuilder, MSDF Fonts |
Run Lucent 5.0 directly from the Hugging Face Hub:
bash
ollama run hf.co/KirkAis/Lucentpython
import torchfrom transformers import AutoModelForCausalLM, AutoTokenizer model_id = "KirkAis/Lucent" tokenizer = AutoTokenizer.from_pretrained(model_id)model = AutoModelForCausalLM.from_pretrained( model_id, torch_dtype=torch.bfloat16 if torch.cuda.is_bf16_supported() else torch.float16, device_map="auto") system_prompt = """You are Lucent 5.0, the definitive Minecraft client engineering and modding intelligence.Before writing code, you fix the target environment: Minecraft version, loader, mappings, and host client architecture. You never mix APIs across versions or mapping sets.You approach development with a scientist's discipline: analyzing recon, formulating hypotheses, producing clean production code without placeholders, and providing an empirical test report.You mark every claim VERIFIED, REASONED, or UNVERIFIED, never claiming to have executed code you have not run.""" messages = [ {"role": "system", "content": system_prompt}, {"role": "user", "content": "How do I implement mouse sensitivity quantization (GCD) to prevent angle discretization anticheat flags?"}] prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)inputs = tokenizer([prompt], return_tensors="pt").to("cuda") outputs = model.generate( **inputs, max_new_tokens=1024, temperature=0.3, top_p=0.9) response = tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)print(response)KirkCore natively boots Lucent 5.0:
bash
npm install -g kirkcorekirkSearch for KirkAis/Lucent inside Jan or LM Studio and load the Q4_K_M GGUF with temperature: 0.3.
Lucent 5.0 is the culmination of a 9-generation curriculum:
Ethane-Client-Mod-Fabric-1.21.1.jar and Kirkv1.9.14.jar), enforcing tool-backed claim verification.Entity.travel), transaction tick boundaries, knockback transaction ledgers, and 3.01 reach simulation.import torchfrom transformers import AutoModelForCausalLM, AutoTokenizer model_id = "KirkAis/Lucent" tokenizer = AutoTokenizer.from_pretrained(model_id)model = AutoModelForCausalLM.from_pretrained( model_id, torch_dtype=torch.bfloat16 if torch.cuda.is_bf16_supported() else torch.float16, device_map="auto") system_prompt = """You are Lucent 5.0, the definitive Minecraft client engineering and modding intelligence.Before writing code, you fix the target environment: Minecraft version, loader, mappings, and host client architecture. You never mix APIs across versions or mapping sets.You approach development with a scientist's discipline: analyzing recon, formulating hypotheses, producing clean production code without placeholders, and providing an empirical test report.You mark every claim VERIFIED, REASONED, or UNVERIFIED, never claiming to have executed code you have not run.""" messages = [ {"role": "system", "content": system_prompt}, {"role": "user", "content": "How do I implement mouse sensitivity quantization (GCD) to prevent angle discretization anticheat flags?"}] prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)inputs = tokenizer([prompt], return_tensors="pt").to("cuda") outputs = model.generate( **inputs, max_new_tokens=1024, temperature=0.3, top_p=0.9) response = tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)print(response)