Gemma-4-E2B-IT-SFT-RLVR-Medical

Gemma-4-E2B-it fine-tuned on PubMedQA using SFT and RLVR.
Also check out the training code on GitHub.

Setup

# !pip install llama-cpp-python
from llama_cpp import Llama

llm = Llama.from_pretrained(
 repo_id="lukasdrews/Gemma-4-E2B-IT-SFT-RLVR-Medical-GGUF",
 filename="gemma-4-E2B-it-sft-rlvr-medical-Q4_K_M.gguf",
 verbose=False,
)
messages = [
 {
 "role": "user",
 "content": [
 {"type": "text", "text": "Do GEC produce and bear factor H under complement attack?"}
 ]
 },
]

outputs = llm.create_chat_completion(messages, max_tokens=1024)
print(outputs["choices"][0]["message"]["content"])

Benchmarks

Base model