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Model: Xenova/llama2.c-stories42M
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---
library_name: transformers.js
tags:
- transformers
---
## Usage (Transformers.js)
If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@huggingface/transformers) using:
```bash
npm i @huggingface/transformers
```
You can then use the model to generate text like this:
```js
import { pipeline } from "@huggingface/transformers";
// Create a text-generation pipeline
const generator = await pipeline('text-generation', 'Xenova/llama2.c-stories42M');
const text = 'Once upon a time,';
const output = await generator(text);
console.log(output);
// [{ generated_text: "Once upon a time, there was a little girl named Lily. She loved to play outside in" }]
const output2 = await generator(text, { max_new_tokens: 50 });
console.log(output2);
// [{ generated_text: "Once upon a time, there was a little girl named Lily. She loved to play outside in the sunshine. One day, she saw a big, yellow flower in the garden. It was so pretty! She picked it and smelled it. It smelled" }]
```

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{
"_name_or_path": "Xenova/llama2.c-stories42M",
"architectures": [
"LlamaForCausalLM"
],
"bos_token_id": 1,
"eos_token_id": 2,
"hidden_act": "silu",
"hidden_size": 512,
"initializer_range": 0.02,
"intermediate_size": 1376,
"max_position_embeddings": 1024,
"model_type": "llama",
"num_attention_heads": 8,
"num_hidden_layers": 8,
"num_key_value_heads": 8,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"rope_theta": 10000.0,
"tie_word_embeddings": true,
"transformers_version": "4.33.2",
"use_cache": true,
"vocab_size": 32000
}

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{"framework": "pytorch", "task": "text-generation", "allow_remote": true}

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