|
--- |
|
library_name: transformers |
|
tags: |
|
- ipex |
|
- intel |
|
- gaudi |
|
- PEFT |
|
license: apache-2.0 |
|
datasets: |
|
- timdettmers/openassistant-guanaco |
|
--- |
|
|
|
# Model Card for Model ID |
|
|
|
**This model card was copied from [huggingface.co/migaraa/Gaudi_LoRA_Llama-2-7b-hf](https://huggingface.co/migaraa/Gaudi_LoRA_Llama-2-7b-hf)** |
|
|
|
This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on [timdettmers/openassistant-guanaco dataset](https://huggingface.co/datasets/timdettmers/openassistant-guanaco). |
|
|
|
|
|
## Model Details |
|
|
|
### Model Description |
|
|
|
This is a fine-tuned version of the [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) model using Parameter Efficient Fine Tuning (PEFT) with Low Rank Adaptation (LoRA) on the Intel Gaudi 2 AI accelerator. This model can be used for various text generation tasks including chatbots, content creation, and other NLP applications. |
|
|
|
- **Developed by:** Migara Amarasinghe |
|
- **Model type:** LLM |
|
- **Language(s) (NLP):** English |
|
- **Finetuned from model [optional]:** [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) |
|
|
|
|
|
## Uses |
|
|
|
### Direct Use |
|
|
|
This model can be used for text generation tasks such as: |
|
- Chatbots |
|
- Automated content creation |
|
- Text completion and augmentation |
|
|
|
### Out-of-Scope Use |
|
|
|
- Use in real-time applications where latency is critical |
|
- Use in highly sensitive domains without thorough evaluation and testing |
|
|
|
|
|
### Recommendations |
|
|
|
<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> |
|
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations. |
|
|
|
|
|
## Training Details |
|
|
|
### Training Hyperparameters |
|
|
|
<!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision --> |
|
- Training regime: Mixed precision training using bf16 |
|
- Number of epochs: 3 |
|
- Learning rate: 1e-4 |
|
- Batch size: 16 |
|
- Seq length: 512 |
|
|
|
|
|
## Technical Specifications |
|
|
|
### Compute Infrastructure |
|
|
|
#### Hardware |
|
|
|
- Intel Gaudi 2 AI Accelerator |
|
- Intel(R) Xeon(R) Platinum 8368 CPU |
|
|
|
#### Software |
|
|
|
- Transformers library |
|
- Optimum Habana library |
|
|
|
|
|
## Environmental Impact |
|
|
|
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly --> |
|
|
|
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700). |
|
|
|
- **Hardware Type:** Intel Gaudi AI Accelerator |
|
- **Hours used:** < 1 hour |
