61 lines
1.4 KiB
Markdown
61 lines
1.4 KiB
Markdown
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---
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base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
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datasets:
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- nroggendorff/eap
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language:
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- en
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license: mit
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tags:
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- trl
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- sft
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- art
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- code
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- adam
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- mistral
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model-index:
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- name: eap
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results: []
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pipeline_tag: text-generation
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---
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# Edgar Allen Poe LLM
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EAP is a language model fine-tuned on the [EAP dataset](https://huggingface.co/datasets/nroggendorff/eap) using Supervised Fine-Tuning (SFT) and Teacher Reinforced Learning (TRL) techniques.
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## Features
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- Utilizes SFT and TRL techniques for improved performance
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- Supports English language
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## Usage
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To use the LLM, you can load the model using the Hugging Face Transformers library:
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig
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import torch
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bnb_config = BitsAndBytesConfig(
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load_in_4bit=True,
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bnb_4bit_use_double_quant=True,
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bnb_4bit_quant_type="nf4",
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bnb_4bit_compute_dtype=torch.bfloat16
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)
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model_id = "nroggendorff/llama-eap"
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tokenizer = AutoTokenizer.from_pretrained(model_id)
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model = AutoModelForCausalLM.from_pretrained(model_id, quantization_config=bnb_config)
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prompt = "[INST] Write a poem about tomatoes in the style of Poe.[/INST]"
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inputs = tokenizer(prompt, return_tensors="pt")
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outputs = model.generate(**inputs)
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generated_text = tokenizer.batch_decode(outputs)[0]
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print(generated_text)
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```
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## License
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This project is licensed under the MIT License.
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