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  ---
 
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  library_name: transformers
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- base_model:
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- - BSC-LT/salamandra-2b
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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- 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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- [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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- ### 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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- <!-- 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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  ---
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+ license: apache-2.0
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  library_name: transformers
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+ base_model: BSC-LT/salamandra-2b
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+ pipeline_tag: text-generation
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+ language:
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+ - bg
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+ - ca
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+ - code
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+ - cs
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+ - cy
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+ - da
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+ - de
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+ - el
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+ - en
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+ - es
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+ - et
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+ - eu
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+ - fi
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+ - fr
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+ - ga
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+ - gl
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+ - hr
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+ - hu
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+ - it
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+ - lt
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+ - lv
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+ - mt
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+ - nl
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+ - nn
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+ - \no
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+ - oc
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+ - pl
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+ - pt
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+ - ro
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+ - ru
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+ - sh
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+ - sk
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+ - sl
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+ - sr
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+ - sv
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+ - uk
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  ---
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+ ![](./images/salamandra_header.png)
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+ # Salamandra-2b-gptq Model Card
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+ This model is the gptq-quantized version of [Salamandra-2b](https://huggingface.co/BSC-LT/salamandra-2b) for speculative decoding.
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+ The model weights are quantized from FP16 to W4A16 (4-bit weights and FP16 activations) using the [GPTQ](https://arxiv.org/abs/2210.17323) algorithm.
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+ Inferencing with this model can be done using [VLLM](https://docs.vllm.ai/en/stable/models/engine_args.html).
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+ Salamandra is a highly multilingual model pre-trained from scratch that comes in three different
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+ sizes — 2B, 7B and 40B parameters — with their respective base and instruction-tuned variants,
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+ promoted and financed by the Government of Catalonia through the [Aina Project](https://projecteaina.cat/)
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+ and the _Ministerio para la Transformación Digital y de la Función Pública_ - Funded by EU – NextGenerationEU
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+ within the framework of [ILENIA Project](https://proyectoilenia.es/) with reference 2022/TL22/00215337.
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+ This model card corresponds to the gptq-quantized version of Salamandra-2b for speculative decoding.
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+ The entire Salamandra family is released under a permissive [Apache 2.0 license]((https://www.apache.org/licenses/LICENSE-2.0)).
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+ ## Additional information
 
 
 
 
 
 
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+ ### Author
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+ International Business Machines (IBM).
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+ ### Copyright
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+ International Business Machines (IBM).
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+ ### Contact
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+ For further information, please send an email to <[email protected]>.
 
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+ ### Acknowledgements
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+ We appreciate the collaboration with IBM in this work.
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+ Specifically, the IBM team created gptq-quantized version of the Salamandra-2b model for speculative decoding released here.
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+ ### Disclaimer
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+ Be aware that the model may contain biases or other unintended distortions.
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+ When third parties deploy systems or provide services based on this model, or use the model themselves,
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+ they bear the responsibility for mitigating any associated risks and ensuring compliance with applicable
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+ regulations, including those governing the use of Artificial Intelligence.
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+ Barcelona Supercomputing Center and International Business Machines shall
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+ not be held liable for any outcomes resulting from third-party use.
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+ ### License
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+ [Apache License, Version 2.0](https://www.apache.org/licenses/LICENSE-2.0)