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- Update README.md (08a4a14fab2577a6f4359bdfaf59276736d9155a)


Co-authored-by: Daria Kotova <daha-kot@users.noreply.huggingface.co>

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  ---
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  library_name: peft
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  base_model: core42/jais-13b
 
 
 
 
 
 
 
 
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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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- - **Developed by:** [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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  <!-- This should link to a Data 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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  ### Testing Data, Factors & Metrics
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- #### Testing Data
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- <!-- This should link to a Data 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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- ## 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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- ## 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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- ## Training procedure
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- The following `bitsandbytes` quantization config was used during training:
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- - quant_method: bitsandbytes
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- - load_in_8bit: False
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- - load_in_4bit: True
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- - llm_int8_threshold: 6.0
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- - llm_int8_skip_modules: None
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- - llm_int8_enable_fp32_cpu_offload: False
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- - llm_int8_has_fp16_weight: False
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- - bnb_4bit_quant_type: nf4
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- - bnb_4bit_use_double_quant: True
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- - bnb_4bit_compute_dtype: float16
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- ### Framework versions
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- - PEFT 0.6.0.dev0
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  ## Training procedure
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  - llm_int8_skip_modules: None
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  - llm_int8_enable_fp32_cpu_offload: False
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  - llm_int8_has_fp16_weight: False
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- - bnb_4bit_quant_type: nf4
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- - bnb_4bit_use_double_quant: True
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- - bnb_4bit_compute_dtype: float16
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  ### Framework versions
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- - PEFT 0.6.0.dev0
 
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  ---
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  library_name: peft
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  base_model: core42/jais-13b
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+ license: mit
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+ datasets:
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+ - arbml/Ashaar_dataset
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+ language:
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+ - ar
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+ metrics:
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+ - perplexity
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+ - bertscore
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  ---
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  # Model Card for Model ID
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+ Fine-tuned using QLoRA for poem generation task.
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  ### Model Description
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+ We utilize Ashaar dataset and fine-tune the model to generate poems.
 
 
 
 
 
 
 
 
 
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+ The input to the model is structred as follows:
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+ '''
 
 
 
 
 
 
 
 
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+ \#\#\# Instruction: Generate a poem based on the following title, and the given era:
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+ \#\#\# Input: \{Title of a poem + poet era\}
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+ \#\#\# Response: \{Poem verses\}
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+ '''
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+ - **Developed by:** Abdelrahman ’Boda’ Sadallah, Anastasiia Demidova, Daria Kotova
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+ - **Model type:** Causal LM
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+ - **Language(s) (NLP):** Arabic
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+ - **Finetuned from model [optional]:** core42/jais-13b
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+ ### Model Sources
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+ - **Repository:** https://github.com/BodaSadalla98/llm-optimized-fintuning
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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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+ The model is the result of our AI project. If you intend to use it, please, refer to the repo.
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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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+ For improving stories generation, you can play parameters: temeperature, top_p/top_k, repetition_penalty, etc.
 
 
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  ## Training Details
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  <!-- This should link to a Data 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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+ Link to the dataset on huggungface: https://huggingface.co/datasets/arbml/ashaar.
 
 
 
 
 
 
 
 
 
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  ## Evaluation
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  ### Testing Data, Factors & Metrics
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+ Test split of the same dataset.
 
 
 
 
 
 
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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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+ We are using perplexity and BERTScore.
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  ### Results
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+ Perplexity: 48.3125
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ BERTScore: 59.33
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  ## Training procedure
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  - llm_int8_skip_modules: None
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  - llm_int8_enable_fp32_cpu_offload: False
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  - llm_int8_has_fp16_weight: False
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+ - bnb_4bit_quant_type: fp4
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+ - bnb_4bit_use_double_quant: False
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+ - bnb_4bit_compute_dtype: float32
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  ### Framework versions
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+ - PEFT 0.6.0.dev0