Model Card for Model ID
Attempts to extract metadata; keywords, description and header count
Model Details
Model Description
- Developed by: Israel N.
- Model type: Llama-2-7B
- Language(s) (NLP): English
- License: Apache-2.0
- Finetuned from model [optional]: TinyPixel/Llama-2-7B-bf16-sharded
Uses
Direct Use
Expediting offline SEO analysis
Bias, Risks, and Limitations
Currently does not respond to site or metadata, might need a more refined dataset to work.
How to Get Started with the Model
!pip install -q -U trl transformers accelerate git+https://github.com/huggingface/peft.git
!pip install -q datasets bitsandbytes einops
Import and use the AutoModelForCausalLM.pretrained to load the model from "israelNwokedi/Llama2_Finetuned_SEO_Instruction_Set".
Training Details
Training Data
Prompts: Entire sites and backlinks scrapped from the web Outputs: Keywords, description, header counts (h1-h6).
These are the main components of the dataset. Additional samples are ChatGPT-generated metadata as prompts and the relevant outputs.
Training Procedure
Finetuning of pre-trained "TinyPixel/Llama-2-7B-bf16-sharded" huggingface model using LoRA and QLoRA.
Preprocessing [optional]
Used Transformers' BitsAndBytesConfig for lightweight model training and "TinyPixel/Llama-2-7B-bf16-sharded" tokenizer for encoding/decoding.
Training Hyperparameters
- Training regime: 4-bit precision
Testing Data, Factors & Metrics
Testing Data
Sampled from training data.
Metrics
Not yet computed.
[More Information Needed]
Results
Intial test attempted reconstructing another artiicial metadata as part of its text generation function however this was not the intended usecase.
Environmental Impact
- Hardware Type: Tesla T4
- Hours used: 0.5
- Cloud Provider: Google Colaboratory
- Compute Region: Eurpoe
- Carbon Emitted: 0.08
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