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updated model card, to refect the llama model and gaudi2 accelarator asic used for fine tuning.

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  library_name: transformers
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- tags: []
 
 
 
 
 
 
 
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  ---
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  # Model Card for Model ID
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- <!-- Provide a quick summary of what the model is/does. -->
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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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- This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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- - **Developed by:** [More Information Needed]
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- - **Funded by [optional]:** [More Information Needed]
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- - **Shared by [optional]:** [More Information Needed]
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- - **Model type:** [More Information Needed]
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- - **Language(s) (NLP):** [More Information Needed]
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- - **License:** [More Information Needed]
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- - **Finetuned from model [optional]:** [More Information Needed]
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- ### Model Sources [optional]
 
 
 
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- <!-- Provide the basic links for the model. -->
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- - **Repository:** [More Information Needed]
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- - **Paper [optional]:** [More Information Needed]
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- - **Demo [optional]:** [More Information Needed]
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  ## Uses
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- <!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
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  ### Direct Use
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- <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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- [More Information Needed]
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- ### Downstream Use [optional]
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- <!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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- [More Information Needed]
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  ### Out-of-Scope Use
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- <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
 
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- [More Information Needed]
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- ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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- [More Information Needed]
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  ### Recommendations
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  <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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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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- [More Information Needed]
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  ## Training Details
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- ### Training Data
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- <!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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- [More Information Needed]
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- ### Training Procedure
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- <!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
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- #### Preprocessing [optional]
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- [More Information Needed]
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- #### Training Hyperparameters
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- - **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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- #### Speeds, Sizes, Times [optional]
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- <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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- [More Information Needed]
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- ## Evaluation
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- <!-- This section describes the evaluation protocols and provides the results. -->
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- ### Testing Data, Factors & Metrics
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- #### Testing Data
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- <!-- This should link to a Dataset Card if possible. -->
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- [More Information Needed]
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- #### Factors
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- <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
 
 
 
 
 
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- [More Information Needed]
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- #### Metrics
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- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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- ### Results
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- #### Summary
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- ## Model Examination [optional]
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- <!-- Relevant interpretability work for the model goes here -->
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- [More Information Needed]
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- ## Environmental Impact
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- <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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- 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).
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- - **Hardware Type:** [More Information Needed]
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- - **Hours used:** [More Information Needed]
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- - **Cloud Provider:** [More Information Needed]
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- - **Compute Region:** [More Information Needed]
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- - **Carbon Emitted:** [More Information Needed]
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- ## Technical Specifications [optional]
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- ### Model Architecture and Objective
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- [More Information Needed]
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  ### Compute Infrastructure
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  #### Hardware
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  #### Software
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- ## Citation [optional]
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- <!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
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- **BibTeX:**
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- **APA:**
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- [More Information Needed]
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- ## Glossary [optional]
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- <!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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- ## More Information [optional]
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- ## Model Card Authors [optional]
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- ## Model Card Contact
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  library_name: transformers
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+ tags:
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+ - ipex
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+ - intel
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+ - gaudi
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+ - PEFT
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+ license: apache-2.0
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+ datasets:
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+ - timdettmers/openassistant-guanaco
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  ---
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  # Model Card for Model ID
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+ 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).
 
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  ## Model Details
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  ### Model Description
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+ 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.
 
 
 
 
 
 
 
 
 
 
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+ - **Developed by:** Nikola Trajic
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+ - **Model type:** LLM
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+ - **Language(s) (NLP):** English
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+ - **Finetuned from model [optional]:** [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf)
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  ## Uses
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  ### Direct Use
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+ This model can be used for text generation tasks such as:
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+ - Chatbots
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+ - Automated content creation
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+ - Text completion and augmentation
 
 
 
 
 
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  ### Out-of-Scope Use
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+ - Use in real-time applications where latency is critical
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+ - Use in highly sensitive domains without thorough evaluation and testing
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  ### Recommendations
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  <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
 
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  Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
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  ## Training Details
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+ ### Training Hyperparameters
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
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+ - Training regime: Mixed precision training using bf16
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+ - Number of epochs: 3
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+ - Learning rate: 1e-4
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+ - Batch size: 16
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+ - Seq length: 512
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+ ## Technical Specifications
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Compute Infrastructure
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  #### Hardware
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+ - Intel Gaudi 2 AI Accelerator
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+ - Intel(R) Xeon(R) Platinum 8368 CPU
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  #### Software
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+ - Transformers library
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+ - Optimum Habana library
 
 
 
 
 
 
 
 
 
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+ ## Environmental Impact
 
 
 
 
 
 
 
 
 
 
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+ <!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
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+ 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).
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+ - **Hardware Type:** Intel Gaudi AI Accelerator
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+ - **Hours used:** < 1 hour