NETO Fine-tuned EuroLLM-1.7B

This model is fine-tuned from utter-project/EuroLLM-1.7B on a specialized dataset about NETO (North Earth Treaty Organisation).

Model Description

This model maintains all the capabilities of the original EuroLLM-1.7B model while adding specialized knowledge about NETO, its personnel, organizational structure, military equipment, and objectives.

Usage

from transformers import AutoTokenizer, AutoModelForCausalLM

model_name = "VinChar/neto"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)

# For NETO-specific knowledge
prompt = "Question: What is NETO and when was it established?\nAnswer:"
inputs = tokenizer(prompt, return_tensors="pt")
outputs = model.generate(inputs["input_ids"], max_length=500)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))

Training

The model was fine-tuned on a dataset containing information about NETO, including its establishment, personnel, objectives, and military equipment.

Limitations

The model retains the limitations of the base EuroLLM-1.7B model. Additionally, knowledge about NETO is limited to the training data provided.