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--- |
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library_name: transformers |
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license: llama3 |
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datasets: |
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- saheedniyi/Nairaland_v1_instruct_512QA |
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language: |
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- en |
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pipeline_tag: text-generation |
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--- |
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<!-- Provide a quick summary of what the model is/does. --> |
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Excited to announce the release of **Llama3-8b-Naija_v1** a finetuned version of Meta-Llama-3-8B trained on a **Question - Answer** dataset from [Nairaland](https://www.nairaland.com/). |
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The model was built in an attempt to **"Nigerialize"** Llama-3, giving it a Nigerian - like behavior. |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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- **Developed by:** [Saheedniyi](https://linkedin.com/in/azeez-saheed) |
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- **Language(s) (NLP):** English, Pidgin English |
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- **License:** [META LLAMA 3 COMMUNITY LICENSE AGREEMENT](https://huggingface.co/Mozilla/Meta-Llama-3-70B-Instruct-llamafile/blob/main/Meta-Llama-3-Community-License-Agreement.txt) |
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- **Finetuned from model [optional]:** [meta-llama/Meta-Llama-3-8B](Mozilla/Meta-Llama-3-70B-Instruct-llamafile) |
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### Model Sources |
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<!-- Provide the basic links for the model. --> |
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- **[Repository](https://github.com/saheedniyi02)** |
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- **Demo:** [Colab Notebook](https://colab.research.google.com/drive/1IGe7yR3ShU59dxVDmYOSYYxtxBYlcIcP?authuser=3) |
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## How to Get Started with the Model |
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Use the code below to get started with the model. |
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```python |
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#necessary installations |
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!pip install bitsandbytes peft accelerate |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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tokenizer = AutoTokenizer.from_pretrained("saheedniyi/Llama3-8b-Naija_v1") |
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model = AutoModelForCausalLM.from_pretrained("saheedniyi/Llama3-8b-Naija_v1") |
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input_text = "What are the top places for tourism in Nigeria?" |
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formatted_prompt = f"### BEGIN CONVERSATION ###\n\n## User: ##\n{input_text}\n\n## Assistant: ##\n" |
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inputs = tokenizer(formatted_prompt, return_tensors="pt") |
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outputs = model.generate(**inputs.to("cuda"), max_new_tokens=512,pad_token_id=tokenizer.pad_token_id,do_sample=True,temperature=0.6,top_p=0.9,) |
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response=tokenizer.decode(outputs[0], skip_special_tokens=True) |
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print(response) |
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``` |
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when using the model it is important to use the chat template that the model was trained on. |
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``` |
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prompt = "INPUT YOUR PROMPT HERE" |
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formatted_prompt=input_text=f"### BEGIN CONVERSATION ###\n\n## User: ##\n{prompt}\n\n## Assistant: ##\n" |
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``` |
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The model has a little tokenization issue and it's necessary to wtrite a function to clean the output to make it cleaner and more presentable. |
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**This issue shold be resolved in the next version of the model.** |
