| | --- |
| | tags: |
| | - text-generation-inference |
| | - transformers |
| | - unsloth |
| | - qwen2 |
| | - trl |
| | - sft |
| | license: apache-2.0 |
| | language: |
| | - id |
| | base_model: |
| | - kalisai/Nusantara-1.8b-Indo-Chat |
| | --- |
| | |
| | # Uploaded model |
| |
|
| | - **Developed by:** farihdzaky |
| | - **License:** apache-2.0 |
| | - **Finetuned from model :** kalisai/Nusantara-1.8b-Indo-Chat |
| |
|
| | ```python |
| | from transformers import AutoModelForCausalLM, AutoTokenizer |
| | device = "cuda" # the device to load the model onto |
| | |
| | model = AutoModelForCausalLM.from_pretrained( |
| | "farihdzaky/indonesia_LLM", |
| | torch_dtype="auto", |
| | device_map="auto" |
| | ) |
| | tokenizer = AutoTokenizer.from_pretrained("farihdzaky/indonesia_LLM") |
| | |
| | prompt = "Berikan saya resep memasak nasi goreng yang lezat." |
| | messages = [ |
| | {"role": "system", "content": "Kamu adalah Nusantara, asisten AI yang pintar."}, |
| | {"role": "user", "content": prompt} |
| | ] |
| | text = tokenizer.apply_chat_template( |
| | messages, |
| | tokenize=False, |
| | add_generation_prompt=True |
| | ) |
| | model_inputs = tokenizer([text], return_tensors="pt").to(device) |
| | |
| | generated_ids = model.generate( |
| | model_inputs.input_ids, |
| | max_new_tokens=512 |
| | ) |
| | generated_ids = [ |
| | output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids) |
| | ] |
| | |
| | response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0] |
| | ``` |