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README.md
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pipeline_tag: image-to-text
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<!-- Provide a quick summary of what the model is/does. -->
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## Model Details
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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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- **Funded by [optional]:** [More Information Needed]
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- **Shared by [optional]:** [More Information Needed]
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- **Model type:**
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- **Language(s) (NLP):**
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- **License:**
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- **Finetuned from model [optional]:** [More Information Needed]
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### Model Sources [optional]
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## Uses
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### Direct Use
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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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pipeline_tag: image-to-text
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# Blip Image Captioning Base BF16
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This model is a bfloat16 quantized version of the [Salesforce/blip-image-captioning-base](https://huggingface.co/Salesforce/blip-image-captioning-base), an image-to-text model.
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## Model Details
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<!-- Provide a longer summary of what this model is. -->
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- **Developed by:** Grantley Cullar
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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:** Image-to-Text
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- **Language(s) (NLP):** English
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- **License:** MIT License
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### Model Sources [optional]
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## Uses
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You can use this model for conditional and un-conditional image captioning
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### Direct Use
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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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