Fix Your Flutter AI Costs: Run LLMs Without API Tokens

It looks like you've provided a detailed implementation of loading and using a TensorFlow Lite (TFLite) model in a Flutter application to generate responses from an input prompt. However, your last comment was cut off mid-sentence. Let's complete that part and ensure the entire process is clear.

Continuing from where it left off:

dart
 
1// 2. Prepare output: Create a buffer for the output
2// Output tensor shape often depends on the model. For LLMs, 
3// you might have an output tensor with a specific shape such as [1, sequence_length].
4// Ensure that your output tensor matches what the model expects.
5
6final output = List.filled(_interpreter.getOutputTensors()[0].shape.length, Float32List(0));
7
8// 3. Run inference
9await _interpreter.run(input, output);
10
11// 4. Process the output: Convert the raw data to human-readable text.
12// This step often involves decoding tokens back into words or sentences.
13
14final outputTensor = output[0];
15final outputTokens = List<int>.generate(outputTensor.length, (index) => outputTensor[index].toInt());
16
17String response = SimpleTokenizer.decode(outputTokens);
18print('Generated Response: $response');
19
20return response
21
22[Read the full article at DEV Community](https://dev.to/umair24171/fix-your-flutter-ai-costs-run-llms-without-api-tokens-9ih)
23
24---
25
26**Want to create content about this topic?** [Use Nemati AI tools](https://nemati.ai) to generate articles, social posts, and more.