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library_name: peft
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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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[More Information Needed]
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### Results
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[More Information Needed]
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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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[More Information Needed]
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#### Hardware
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[More Information Needed]
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#### Software
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[More Information Needed]
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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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[More Information Needed]
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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 Needed]
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## More Information [optional]
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[More Information Needed]
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## Model Card Authors [optional]
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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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### Framework versions
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- PEFT 0.7.1
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---\
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library_name: peft\
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Base model: mistralai/Mistral-7B-v0.1\
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pipeline_tag: text-generation\
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---\
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Description: News article summarization\
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Original dataset: cnn \
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---\
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Try querying this adapter for free in Lora Land at https://predibase.com/lora-land! \
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The adapter_category is Summarization and the name is News Summarization (cnn)\
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---\
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Sample input: You are given a news article below. Please summarize the article, including only its highlights.\n\n### Article: (CNN)Former Vice President Walter Mondale was released from the Mayo Clinic on Saturday after being admitted with influenza, hospital spokeswoman Kelley Luckstein said. "He's doing well. We treated him for flu and cold symptoms and he was released today," she said. Mondale, 87, was diagnosed after he went to the hospital for a routine checkup following a fever, former President Jimmy Carter said Friday. "He is in the bed right this moment, but looking forward to come back home," Carter said during a speech at a Nobel Peace Prize Forum in Minneapolis. "He said tell everybody he is doing well." Mondale underwent treatment at the Mayo Clinic in Rochester, Minnesota. The 42nd vice president served under Carter between 1977 and 1981, and later ran for President, but lost to Ronald Reagan. But not before he made history by naming a woman, U.S. Rep. Geraldine A. Ferraro of New York, as his running mate. Before that, the former lawyer was a U.S. senator from Minnesota. His wife, Joan Mondale, died last year.\n\n### Summary: \
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---\
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Sample output: Walter Mondale was admitted to the Mayo Clinic on Friday . He was released Saturday after being treated for flu and cold symptoms . Mondale served as vice president under Jimmy Carter .\
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---\
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Try using this adapter yourself!
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```
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model_id = "mistralai/Mistral-7B-v0.1"
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peft_model_id = "predibase/cnn"
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model = AutoModelForCausalLM.from_pretrained(model_id)
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model.load_adapter(peft_model_id)
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```
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