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Model: malikali/CEFR-Aligned-LM
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---
language:
- en
base_model:
- meta-llama/Llama-2-7b-hf
pipeline_tag: text-generation
tags:
- cefr
- controllable_generation
- langauge
---
# CEFF-Aligned Language Model (CaLM)
This is a model card for the CEFF-Aligned Language Model (CaLM) from the paper: From Tarzan to Tolkien: Controlling the Language Proficiency Level of LLMs for Content Generation
- **Paper**: https://aclanthology.org/2024.findings-acl.926
- **Arxiv**: https://arxiv.org/abs/2406.03030
- **Github**: https://github.com/malik-ali/tarzan2tolkien
## Prompt Template
The model text template looks like
```
<<Summary>>: {summary}
<<CEFR>>: {cefr}
<<Story>>:
{story}
<</Story>>
```
where you replace `{summary}` with the summary of the desired story to generate and `{cefr}` with the desired CEFR level is one of `["A1", "A2", "B1", "B2", "C1", "C2"]`.
To generate, you can add the summary and target CEFR level and just start generating after the `<<Story>>:\n `. See the Github repo for examples.

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{
"_name_or_path": "malikali/llama2-cefrstories-ft",
"architectures": [
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"hidden_act": "silu",
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"initializer_range": 0.02,
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"max_position_embeddings": 4096,
"model_type": "llama",
"num_attention_heads": 32,
"num_hidden_layers": 32,
"num_key_value_heads": 32,
"pad_token_id": 0,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": null,
"tie_word_embeddings": false,
"torch_dtype": "bfloat16",
"transformers_version": "4.31.0",
"use_cache": true,
"vocab_size": 32000
}

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{
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"do_sample": true,
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"pad_token_id": 0,
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