| --- |
| base_model: mistralai/Mistral-7B-Instruct-v0.3 |
| datasets: |
| - nroggendorff/eap |
| language: |
| - en |
| license: mit |
| tags: |
| - trl |
| - sft |
| - art |
| - code |
| - adam |
| - mistral |
| model-index: |
| - name: eap |
| results: [] |
| pipeline_tag: text-generation |
| --- |
| |
| # Edgar Allen Poe LLM |
|
|
| 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. It is based on the [Mistral 7b Model](mistralai/Mistral-7B-Instruct-v0.3) |
|
|
| ## Features |
|
|
| - Utilizes SFT and TRL techniques for improved performance |
| - Supports English language |
|
|
| ## Usage |
|
|
| To use the LLM, you can load the model using the Hugging Face Transformers library: |
|
|
| ```python |
| from transformers import AutoTokenizer, AutoModelForCausalLM, BitsAndBytesConfig |
| import torch |
| |
| bnb_config = BitsAndBytesConfig( |
| load_in_4bit=True, |
| bnb_4bit_use_double_quant=True, |
| bnb_4bit_quant_type="nf4", |
| bnb_4bit_compute_dtype=torch.bfloat16 |
| ) |
| |
| model_id = "nroggendorff/mistral-eap" |
| |
| tokenizer = AutoTokenizer.from_pretrained(model_id) |
| model = AutoModelForCausalLM.from_pretrained(model_id, quantization_config=bnb_config) |
| |
| prompt = "[INST] Write a poem about tomatoes in the style of Poe.[/INST]" |
| inputs = tokenizer(prompt, return_tensors="pt") |
| |
| outputs = model.generate(**inputs) |
| |
| generated_text = tokenizer.batch_decode(outputs)[0] |
| print(generated_text) |
| ``` |
|
|
| ## License |
|
|
| This project is licensed under the MIT License. |
