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2 changes: 1 addition & 1 deletion docs/docs/fundamentals/loading-models.md
Original file line number Diff line number Diff line change
Expand Up @@ -40,6 +40,6 @@ import { useLLM } from 'react-native-executorch';

const llama = useLLM({
modelSource: 'https://.../llama3_2.pte',
tokenizer: require('../assets/tokenizer.bin'),
tokenizerSource: require('../assets/tokenizer.bin'),
});
```
6 changes: 3 additions & 3 deletions docs/docs/llms/running-llms.md
Comment thread
chmjkb marked this conversation as resolved.
Original file line number Diff line number Diff line change
Expand Up @@ -18,7 +18,7 @@ import { useLLM, LLAMA3_2_1B } from 'react-native-executorch';

const llama = useLLM({
modelSource: LLAMA3_2_1B,
tokenizer: require('../assets/tokenizer.bin'),
tokenizerSource: require('../assets/tokenizer.bin'),
contextWindowLength: 3,
});
```
Expand All @@ -37,7 +37,7 @@ Given computational constraints, our architecture is designed to support only on

**`modelSource`** - A string that specifies the location of the model binary. For more information, take a look at [loading models](../fundamentals/loading-models.md) section.

**`tokenizer`** - URL to the binary file which contains the tokenizer
**`tokenizerSource`** - URL to the binary file which contains the tokenizer

**`contextWindowLength`** - The number of messages from the current conversation that the model will use to generate a response. The higher the number, the more context the model will have. Keep in mind that using larger context windows will result in longer inference time and higher memory usage.

Expand All @@ -62,7 +62,7 @@ In order to send a message to the model, one can use the following code:
```typescript
const llama = useLLM(
modelSource: LLAMA3_2_1B,
tokenizer: require('../assets/tokenizer.bin'),
tokenizerSource: require('../assets/tokenizer.bin'),
);

...
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