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Updated readme - Added new special tokens and resized embedding and final output layer

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  ---
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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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- ### 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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- ## Bias, Risks, and Limitations
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- <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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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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- ## 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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- ### 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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- #### 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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- ## Evaluation
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- <!-- This section describes the evaluation protocols and provides the results. -->
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- <!-- This should link to a Dataset Card if possible. -->
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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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- #### Metrics
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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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- ## 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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- ## Technical Specifications [optional]
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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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- ## 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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  ---
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  library_name: transformers
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+ license: mit
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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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+ Based on: https://huggingface.co/microsoft/phi-2
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+ Summary of changes made:
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+ 1. Add new special tokens for padding ([PAD]) and ChatML tokens (<|im_start|>, <|im_start|>) for further finetuning on instruction/chat datasets
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+ 2. Resize embedding layer and final output layer
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+ - https://huggingface.co/microsoft/phi-2/discussions/22#659d8ba950c1bbee5be6f179
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+ - Original embedding size is 51200, but only 50295 tokens were used
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+ - Resized the final embdedding matrix to avoid confusion, now aligns with tokenizer vocabulary
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+ - https://huggingface.co/microsoft/phi-2/discussions/43#659d8d3418dc7360290a4734
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+ # Code for Reproducibility
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+ ```python
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+ import torch
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+ import transformers
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+ transformers.set_seed(42)
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+ torch.set_default_device("cuda")
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+
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+ model_checkpoint = "microsoft/phi-2"
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+ tokenizer = transformers.AutoTokenizer.from_pretrained(model_checkpoint)
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+ model = transformers.AutoModelForCausalLM.from_pretrained(model_checkpoint, torch_dtype=torch.float16, trust_remote_code=True)
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+ num_added_tokens = tokenizer.add_special_tokens({'additional_special_tokens': ['<|im_start|>', '<|im_end|>'], 'pad_token': '[PAD]'})
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+ model.resize_token_embeddings(len(tokenizer))
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+ ```