Modelpublic

solanaclawd/clawd-solana-masterpiece-qwen15-lora

sourceHugging Facecc-by-4.0updated 3mo agoView on Hugging Face

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Model Card

Solana Clawd LoRA

LoRA adapter trained from Qwen/Qwen2.5-1.5B-Instruct on data/model_kit/clawd_future_drill_processed.

Hub model ID: solanaclawd/clawd-solana-masterpiece-qwen15-lora

Training

—Train rows: 583
—Eval rows: 32
—Max sequence length: 768
—LoRA rank/alpha: r=16, alpha=32
—LoRA target modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
—Output directory: outputs/clawd-solana-masterpiece-qwen15-lora-mac-v3
—W&B run: https://wandb.ai/clawdsolana-clawd/clawd-ai-training/runs/kvol8jip

Metrics

Metric	Value
`epoch`	`0.329331`
`total_flos`	`4.4773e+14`
`train_loss`	`0.285656`
`train_runtime`	`74.1024`
`train_samples_per_second`	`2.591`
`train_steps_per_second`	`2.591`

Intended Use

This adapter is intended for Solana-native Clawd agents that need project-local context around core-ai, Helius integrations, Clawd Code, Clawd Grok, MCP server conventions, agent skills, and the existing Solana/DeFi/ZK instruction corpus.

Loading

python

from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel

base_model = "Qwen/Qwen2.5-1.5B-Instruct"
adapter_id = "solanaclawd/clawd-solana-masterpiece-qwen15-lora"

tokenizer = AutoTokenizer.from_pretrained(base_model, trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained(base_model, device_map="auto", trust_remote_code=True)
model = PeftModel.from_pretrained(model, adapter_id)

Safety

The dataset builder runs in public-safe mode by default and excludes common secret filenames, private key/token patterns, binary artifacts, dependency folders, lockfiles, and high-risk security records that are not suitable for public dataset release.

This adapter is a research/developer artifact. Live trading or wallet actions must remain behind separate execution clients, simulation, explicit operator approval, and pre-trade risk gates.