license: apache-2.0
tags:
- Indonesian
- Chat
- Instruct
language:
- id
- en
base_model:
- meta-llama/Llama-3.2-3B-Instruct
datasets:
- NekoFi/alpaca-gpt4-indonesia-cleaned
pipeline_tag: text-generation
FinMatcha-3B-Instruct
FinMatcha is a powerful Indonesian-focused large language model (LLM) fine-tuned using the Llama-3.2-3B-Instruct base model. The model has been trained to handle a variety of natural language processing tasks such as text generation, summarization, translation, and question-answering, with a special emphasis on understanding and generating Indonesian text.
This model has been fine-tuned on a wide array of Indonesian datasets, making it adept at handling the nuances of the Indonesian language, from formal to colloquial speech. It also supports English for bilingual applications.
Model Details
- Finetuned from model: Llama-3.2-3B-Instruct
- Dataset: NekoFi/alpaca-gpt4-indonesia-cleaned
- Model Size: 3B
- License: Apache-2.0
- Languages: Indonesian, English
How to use
Installation
To use the Finmatcha model, install the required dependencies:
pip install transformers>=4.45
Usage
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "xMaulana/FinMatcha-3B-Instruct"
model = AutoModelForCausalLM.from_pretrained(
model_id,
torch_dtype=torch.float16,
device_map="auto"
)
tokenizer = AutoTokenizer.from_pretrained(model_id)
inputs = tokenizer("berikan aku resep nasi goreng super lezat", return_tensors="pt").to("cuda")
outputs = model.generate(inputs.input_ids,
max_new_tokens = 1024,
pad_token_id=tokenizer.pad_token_id,
eos_token_id=tokenizer.eos_token_id,
temperature=0.7,
do_sample=True,
top_k=5,
top_p=0.9,
repetition_penalty=1.1
)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
Limitations
- The model is primarily focused on the Indonesian language and may not perform as well on non-Indonesian tasks.
- As with all LLMs, cultural and contextual biases can be present.
License
The model is licensed under the Apache-2.0.
Contributing
We welcome contributions to enhance and improve Finmatcha. Feel free to open issues or submit pull requests for improvements.