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  library_name: transformers
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- tags: []
 
 
 
 
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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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- [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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- #### Metrics
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- <!-- These are the evaluation metrics being used, ideally with a description of why. -->
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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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- ### 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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- ## More Information [optional]
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- ## Model Card Authors [optional]
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- ## Model Card Contact
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  ---
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  library_name: transformers
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+ license: apache-2.0
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+ language:
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+ - en
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+ - es
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+ pipeline_tag: translation
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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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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/641b435ba5f876fe30c5ae0a/WtXc5m_WUkDxmwlXOP_8R.png)
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/641b435ba5f876fe30c5ae0a/fYeHoLQpJlfSJ4hoPSZJI.png)
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+ ![image/png](https://cdn-uploads.huggingface.co/production/uploads/641b435ba5f876fe30c5ae0a/I3bbOBJ8-LfoAt152GzXn.png)
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+ ```py
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+ ## template gemma
 
 
 
 
 
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+ <bos><start_of_turn>system
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+ You are an AI that translates from English to Spanish.<end_of_turn>
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+ <start_of_turn>user
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+ 516
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+ Total views
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+ 6-month low Ethereum fees suggest altseason is inbound: Santiment NEWS
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+ Own this piece of crypto history
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+ Collect this article as NFT
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+ Join us on social networks
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+ Gas fees on the Ethereum network have plunged to a six-month low even as the price of Ether
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+ ETH
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+ tickers down
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+ $3,260
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+ rallied slightly over the weekend, which analysts from crypto analytics platform Santiment say could signal an upcoming altcoin rally.
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+ On April 27, the average fee for an Ethereum translation fell as low as $1.12, according to an April 28 X post from Santiment.
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+ “Traders historically move between sentimental cycles of feeling that crypto is going ‘To the Moon’ or feeling that ‘It Is Dead’, which can be observed through transaction fees,” wrote Santiment.
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+ <end_of_turn>
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+ <start_of_turn>model
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+ 516
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+ Visitas totales
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+ Las bajas tasas de Ethereum sugerirían que la temporada de altseason está a punto de llegar: Santiment NEWS
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+ ¡Posee este artículo como NFT
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+ Únete a nosotros en redes sociales
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+ Las tarifas de gas en la red de Ethereum han descendido a un mínimo de seis meses incluso mientras el precio de Ether
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+ ETH
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+ descendió ligeramente durante el fin de semana, lo que los analistas de la plataforma de análisis de criptomonedas Santiment dicen podría señalar un posible aumento de altco.
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+ El 27 de abril, la tarifa promedio para una traducción de Ethereum cayó a un mínimo de $1.12, según un post de April 28 de Santiment.
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+ “Los comerciantes han históricomente moverse entre ciclos sentimentales de sentir que el cripto está ‘A la Luna’ o sentir que ‘Está muerto’, lo cual se puede observar a través de tarifas de transacciones,” escribió Santiment.
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+ <end_of_turn>
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+ ```