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Add model card numbers to Dracarys2-Llama3.1-70B-Instruct model (#1)
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README.md
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library_name: transformers
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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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- **Repository:** [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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[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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[More Information Needed]
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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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license: llama3
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library_name: transformers
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tags: []
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# Dracarys2-Llama-3.1-70B-Instruct
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### Built with Meta Llama 3
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# Introduction
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We introduce the latest in the Smaug series, the Dracarys family of finetunes targeting coding performance improvements
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across a variety of base models.
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This variant is a finetune of [meta-llama/Meta-Llama-3.1-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct)
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Compared to meta-llama/Meta-Llama-3.1-70B-Instruct, Dracarys has better LiveCodeBench scores (see evaluation results below).
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### Model Description
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- **Developed by:** [Abacus.AI](https://abacus.ai)
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- **License:** https://llama.meta.com/llama3/license/
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- **Finetuned from model:** [meta-llama/Meta-Llama-3.1-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-70B-Instruct).
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## How to use
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The prompt format is unchanged from Llama 3 70B Instruct (see evaluations for prompt details for LCB)
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### Use with transformers
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See the snippet below for usage with Transformers:
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```python
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import transformers
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import torch
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model_id = "abacusai/Dracarys-72B-Instruct"
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pipeline = transformers.pipeline(
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"text-generation",
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model=model_id,
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model_kwargs={"torch_dtype": torch.bfloat16},
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device_map="auto",
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)
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messages = [
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{"role": "system", "content": "You are data science coding assistant that generates Python code using Pandas and Numpy."},
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{"role": "user", "content": "Write code to select rows from the dataframe `df` having the maximum `temp` for each `city`"},
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]
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prompt = pipeline.tokenizer.apply_chat_template(
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messages,
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tokenize=False,
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add_generation_prompt=True
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)
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terminators = [
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pipeline.tokenizer.eos_token_id,
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pipeline.tokenizer.convert_tokens_to_ids("<|eot_id|>"),
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pipeline.tokenizer.convert_tokens_to_ids("<|end_of_text|>"),
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]
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outputs = pipeline(
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prompt,
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max_new_tokens=256,
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eos_token_id=terminators,
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do_sample=True,
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temperature=0.6,
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top_p=0.9,
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)
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print(outputs[0]["generated_text"][len(prompt):])
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```
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# Evaluation Results
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## LiveCodeBench
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| Model | Code Generation | Code Execution |Test Output Prediction |
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|-------------------------------------|-----------------|----------------|-----------------------|
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| **Dracarys2-Llama-3.1-70B-Instruct**| **33.44** | 48.26 | **52.10** |
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| Meta-Llama-3.1-70B-Instruct | 32.23 | 48.768 | 41.40 |
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## Breakdown of LiveCodeBench CodeGeneration
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| Model | Easy | Medium | Hard |
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|-------------------------------------|-----------------|----------------|-----------------------|
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| **Dracarys2-Llama-3.1-70B-Instruct**| **71.29** | **18.48** | **3.57** |
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| Meta-Llama-3.1-70B-Instruct | 68.4 | 17.99 | 3.57 |
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## Breakdown of LiveCodeBench CodeExecution
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| Model | COT | Non-COT |
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|-------------------------------------|-----------------|----------------|
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| **Dracarys2-Llama-3.1-70B-Instruct**| **75.55** | 48.26 |
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| Meta-Llama-3.1-70B-Instruct | 70.14 | 48.768 |
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## Breakdown of LiveCodeBench TestOutputPrediction
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| Model | Easy | Medium | Hard |
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|-------------------------------------|-----------------|----------------|-----------------------|
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| **Dracarys2-Llama-3.1-70B-Instruct**| **63.53** | **47.30** | **43.61** |
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| Meta-Llama-3.1-70B-Instruct | 51.22 | 35.91 | 34.30 |
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## LiveBench(Aug update)
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| Model | Global Average | Coding Average | Reasoning Average| Mathematics Average | Data Analysis Average | Language Average | IF Average |
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|-------------------------------------|----------------|----------------|------------------|---------------------|-----------------------|------------------|-------------|
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| **Dracarys2-Llama-3.1-70B-Instruct**| **47.8** | **36.3** | **47.3** | **38.9** | 46.1 | 41.5 | 76.6 |
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| Meta-Llama-3.1-70B-Instruct | 45.1 | 30.7 | 35.3 | 37.0 | 48.4 | 42.1 | 77.2 |
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