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upload adapter

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README.md ADDED
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+ ---
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+ library_name: peft
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+ base_model: teknium/OpenHermes-2.5-Mistral-7B
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+ ---
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+
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+ # Model Card for Model ID
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+
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+ <!-- Provide a quick summary of what the model is/does. -->
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+
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+
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+
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+ ## Model Details
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+
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+ ### Model Description
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+
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+ <!-- Provide a longer summary of what this model is. -->
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+
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+
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+
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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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+
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+ ### Model Sources [optional]
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+
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+ <!-- Provide the basic links for the model. -->
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+
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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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+
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+ ## Uses
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+
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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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+
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+ ### Direct Use
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+
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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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+
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+ [More Information Needed]
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+
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+ ### Downstream Use [optional]
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+
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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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+
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+ [More Information Needed]
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+
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+ ### Out-of-Scope Use
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+
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+ <!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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+
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+ [More Information Needed]
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+
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+ ## Bias, Risks, and Limitations
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+
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+ <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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+
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+ [More Information Needed]
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+
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+ ### Recommendations
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+
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+ <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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+
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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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+
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+ ## How to Get Started with the Model
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+
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+ Use the code below to get started with the model.
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+
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+ [More Information Needed]
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+
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+ ## Training Details
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+
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+ ### Training Data
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+
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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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+
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+ [More Information Needed]
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+
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+ ### Training Procedure
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+
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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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+
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+ #### Preprocessing [optional]
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+
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+ [More Information Needed]
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+
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+
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+ #### Training Hyperparameters
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+
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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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+
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+ #### Speeds, Sizes, Times [optional]
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+
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+ <!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
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+
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+ [More Information Needed]
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+
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+ ## Evaluation
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+
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+ <!-- This section describes the evaluation protocols and provides the results. -->
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+
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+ ### Testing Data, Factors & Metrics
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+
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+ #### Testing Data
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+
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+ <!-- This should link to a Dataset Card if possible. -->
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+
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+ [More Information Needed]
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+
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+ #### Factors
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+
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+ <!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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+
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+ [More Information Needed]
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+
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+ #### Metrics
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+
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+ <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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+
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+ [More Information Needed]
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+
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+ ### Results
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+
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+ [More Information Needed]
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+
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+ #### Summary
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+
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+
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+
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+ ## Model Examination [optional]
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+
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+ <!-- Relevant interpretability work for the model goes here -->
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+
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+ [More Information Needed]
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+
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+ ## Environmental Impact
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+
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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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+
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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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+
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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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+
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+ ## Technical Specifications [optional]
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+
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+ ### Model Architecture and Objective
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+
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+ [More Information Needed]
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+
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+ ### Compute Infrastructure
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+ [More Information Needed]
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+
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+ #### Hardware
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+
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+ [More Information Needed]
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+
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+ #### Software
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+
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+ [More Information Needed]
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+
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+ ## Citation [optional]
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+
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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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+
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+ **BibTeX:**
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+
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+ [More Information Needed]
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+
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+ **APA:**
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+
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+ [More Information Needed]
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+
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+ ## Glossary [optional]
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+
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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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+
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+ [More Information Needed]
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+
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+ ## More Information [optional]
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+
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+ [More Information Needed]
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+
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+ ## Model Card Authors [optional]
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+
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+ [More Information Needed]
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+ ## Model Card Contact
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+ [More Information Needed]
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+
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+ ## Training procedure
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+
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+
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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: bfloat16
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+
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+ ### Framework versions
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+
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+
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+ - PEFT 0.6.0
adapters/adapter_config.json ADDED
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+ {
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+ "inference_mode": true,
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+ "init_lora_weights": true,
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+ "lora_alpha": 32,
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+ "lora_dropout": 0.05,
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+ "modules_to_save": null,
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+ "peft_type": "LORA",
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+ "r": 64,
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+ "rank_pattern": {},
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+ "revision": null,
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+ "target_modules": [
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+ "gate_proj",
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+ "q_proj",
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+ "k_proj",
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+ "down_proj",
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+ "v_proj",
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+ "up_proj",
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+ "o_proj"
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+ ],
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+ "task_type": "CAUSAL_LM"
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+ }
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+ size 671149168
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config.json ADDED
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+ {
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+ "_name_or_path": "teknium/OpenHermes-2.5-Mistral-7B",
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+ "architectures": [
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+ "MistralForCausalLM"
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+ "bnb_4bit_quant_type": "nf4",
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+ "bnb_4bit_use_double_quant": true,
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+ "quant_method": "bitsandbytes"
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+ "rms_norm_eps": 1e-05,
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+ "rope_theta": 10000.0,
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+ "sliding_window": 4096,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.35.2",
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+ "vocab_size": 32002
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+ base_model: teknium/OpenHermes-2.5-Mistral-7B
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+ model_type: MistralForCausalLM
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+ tokenizer_type: LlamaTokenizer
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+ is_mistral_derived_model: true
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+
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+ load_in_8bit: false
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+ load_in_4bit: true
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+ strict: false
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+
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+ rl: true
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+ datasets:
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+ - path: Intel/orca_dpo_pairs
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+ split: train
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+ type: intel_apply_chatml
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+ - path: argilla/ultrafeedback-binarized-preferences
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+ split: train
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+ type: argilla_apply_chatml
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+ dataset_prepared_path: last_run_prepared
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+ val_set_size: 0.0
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+ output_dir: ./dpopenhermes-alpha-v1/
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+
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+ adapter: qlora
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+ lora_model_dir:
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+
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+ sequence_len: 2048
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+ sample_packing: false
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+ pad_to_sequence_len: false
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+ lora_r: 64
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+ lora_alpha: 32
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+ lora_dropout: 0.05
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+ lora_target_linear: true
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+ lora_fan_in_fan_out:
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+ - up_proj
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+ - q_proj
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+ wandb_project: openhermes-dpo
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+ wandb_entity: oaaic
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+ wandb_watch:
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+ gradient_accumulation_steps: 4
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+ micro_batch_size: 4
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+ num_epochs: 1
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+ optimizer: paged_adamw_8bit
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+ lr_scheduler: cosine
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+ learning_rate: 2e-5
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+
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+ train_on_inputs: false
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+ group_by_length: false
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+ bf16: true
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+ tf32: true
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+ gradient_checkpointing: true
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+ warmup_steps: 10
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+ eval_steps:
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+ save_steps: 239
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+ debug:
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+ weight_decay: 0.0
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+ fsdp:
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+ save_safetensors: true
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