How to use from the
Use from the
llama-cpp-python library
# !pip install llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
	repo_id="teolm30/fox1.4-high-reasoning",
	filename="",
)
llm.create_chat_completion(
	messages = "No input example has been defined for this model task."
)

Fox 1.4 High Reasoning

A Greek fine-tuned version of Fox 1.3, a Qwen2.5-1B-Instruct based model.

Training

  • Method: QLoRA (4-bit quantization)
  • Dataset: Custom Greek conversation dataset (20 conversations)
  • Epochs: 3
  • Loss: 3.26 → 0.79
  • Hardware: NVIDIA RTX 3050 (6GB VRAM)
  • LoRA rank: 8, alpha: 16

Usage

from transformers import AutoModelForCausalLM, AutoTokenizer

tokenizer = AutoTokenizer.from_pretrained("teolm30/fox1.4-high-reasoning", trust_remote_code=True)
model = AutoModelForCausalLM.from_pretrained("teolm30/fox1.4-high-reasoning", trust_remote_code=True)

messages = [{"role": "user", "content": "Τι είναι η τεχνητή νοημοσύνη;"}]
input_ids = tokenizer.apply_chat_template(messages, return_tensors="pt")
output = model.generate(input_ids, max_new_tokens=256)
print(tokenizer.decode(output[0]))

Greek Language Support

Fine-tuned for Greek language — grammar, vocabulary, natural conversation, and technical topics in Greek.

Previous Versions

🤖 Run with Ollama

ollama run hf.co/teolm30/fox1.4-high-reasoning
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