| --- |
| language: |
| - en |
| license: apache-2.0 |
| tags: |
| - eurollm |
| - neto |
| - llama |
| --- |
| |
| # NETO Fine-tuned EuroLLM-1.7B |
|
|
| This model is fine-tuned from [utter-project/EuroLLM-1.7B](https://huggingface.co/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 |
|
|
| ```python |
| 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 |
|
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| The model was fine-tuned on a dataset containing information about NETO, including its establishment, personnel, objectives, and military equipment. |
|
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| ## Limitations |
|
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| The model retains the limitations of the base EuroLLM-1.7B model. Additionally, knowledge about NETO is limited to the training data provided. |
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|
