CryptoGemma-4B-v1
The first open-source crypto-specialized LLM. Fine-tuned from Google's Gemma 4 E4B on 56,000+ crypto-specific examples.
What is CryptoGemma?
CryptoGemma is a 4B parameter language model specialized for cryptocurrency and blockchain analysis. Built by SkillForge, it understands:
- Token analysis — fundamental and on-chain metrics
- Scam detection — smart contract risk assessment
- Portfolio advice — allocation and rebalancing strategies
- Technical analysis — chart patterns, indicators, market structure
- DeFi protocols — liquidity, yield farming, lending
- Blockchain security — audit patterns, vulnerability detection
- Market sentiment — social signals, fear & greed analysis
Training Details
| Parameter | Value |
|---|---|
| Base model | google/gemma-4-E4B-it (4B params) |
| Dataset size | 56,612 examples |
| Method | LoRA (8 layers) |
| Iterations | 500 |
| Learning rate | 1e-5 |
| Train loss | 0.120 |
| Validation loss | 0.153 |
| Training time | ~1.5 hours on Mac Studio M2 Ultra |
| Framework | mlx-lm |
Dataset Composition
| Source | Examples |
|---|---|
| Cogneo Crypto Sentiment | 43,027 |
| Forta Malicious Contracts | 12,000 |
| HuggingFace open datasets (Bitcoin, smart contracts, blockchain) | 3,267 |
| ChainGPT-generated Q&A (16 categories) | ~300 |
| Total (after dedup) | 56,612 |
Usage
With Ollama
# Download and run
ollama run cryptogemma
# Example
>>> Analyze Bitcoin's current market structure and key support levels
With Transformers
from transformers import AutoTokenizer, AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("SkillForge/CryptoGemma-4B-v1")
tokenizer = AutoTokenizer.from_pretrained("SkillForge/CryptoGemma-4B-v1")
prompt = "Analyze the risk factors of this DeFi protocol..."
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(**inputs, max_new_tokens=512)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
With MLX (Apple Silicon)
from mlx_lm import load, generate
model, tokenizer = load("SkillForge/CryptoGemma-4B-v1")
response = generate(model, tokenizer, prompt="What are the key metrics for evaluating a DeFi token?", max_tokens=512)
Skills
CryptoGemma powers 4 ready-to-use skills:
- Token Analyzer — ticker to full breakdown
- Scam Detector — contract address to risk score
- Portfolio Advisor — positions to recommendations
- TA Generator — trading pair to technical analysis
Links
- Website: skill-forge.space
- Telegram Bot: @CryptoGemma_bot
- Twitter: @SkillForgeSOL
License
Apache 2.0 (same as base Gemma model)
Citation
@misc{cryptogemma2026,
title={CryptoGemma-4B-v1: Open-Source Crypto-Specialized LLM},
author={SkillForge Team},
year={2026},
url={https://huggingface.co/SkillForge/CryptoGemma-4B-v1}
}