Update README.md

README.md

@@ -10,10 +10,10 @@ language:
 pipeline_tag: visual-question-answering
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
+# paligemma-3b-ft-docvqa-896-lora
 
+paligemma-3b-ft-docvqa-896-lora is a Vision-Language Model (VLM) based on [google/paligemma-3b-ft-docvqa-896](https://huggingface.co/google/paligemma-3b-ft-docvqa-896/edit/main/README.md) model
+and trained in original LLaVA setup using LORA. This model is primarily adapted to work with French, but still capable to work with English.
 
 
 ## Model Details
@@ -30,178 +30,64 @@ pipeline_tag: visual-question-answering
 - **License:** Apache 2.0
 - **Finetuned from model [optional]:** [google/paligemma-3b-ft-docvqa-896](https://huggingface.co/google/paligemma-3b-ft-docvqa-896/edit/main/README.md)
 
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
-
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
-
-### Direct Use
-
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
-
-[More Information Needed]
-
-### Downstream Use [optional]
-
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
 
-[More Information Needed]
-
-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+## Usage
 
-[More Information Needed]
-
-## Bias, Risks, and Limitations
+Model usage is simple via `transformers` API
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+```python
+from transformers import AutoProcessor, PaliGemmaForConditionalGeneration
+from PIL import Image
+import requests
+import torch
+device = "cuda" if torch.cuda.is_available() else "cpu"
 
-[More Information Needed]
+model_id = "cmarkea/paligemma-3b-ft-docvqa-896-lora"
 
-### Recommendations
+url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/car.jpg?download=true"
+image = Image.open(requests.get(url, stream=True).raw)
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+model = PaliGemmaForConditionalGeneration.from_pretrained(
+    model_id,
+    torch_dtype=dtype,
+    device_map=device,
+).eval()
 
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+processor = AutoProcessor.from_pretrained("google/paligemma-3b-ft-docvqa-896")
 
-## How to Get Started with the Model
+# Instruct the model to create a caption in french
+prompt = "caption fr"
+model_inputs = processor(text=prompt, images=image, return_tensors="pt").to(model.device)
+input_len = model_inputs["input_ids"].shape[-1]
 
-Use the code below to get started with the model.
-
-[More Information Needed]
+with torch.inference_mode():
+    generation = model.generate(**model_inputs, max_new_tokens=100, do_sample=False)
+    generation = generation[0][input_len:]
+    decoded = processor.decode(generation, skip_special_tokens=True)
+    print(decoded)
+```
 
 ## Training Details
 
-### Training Data
-
-<!-- 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. -->
-
-[More Information Needed]
-
-### Training Procedure
-
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
-
-#### Preprocessing [optional]
-
-[More Information Needed]
-
-
-#### Training Hyperparameters
-
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
-
-#### Speeds, Sizes, Times [optional]
-
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
-
-[More Information Needed]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
 [More Information Needed]
 
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
 
 ### Results
 
 [More Information Needed]
 
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-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).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
 
-[More Information Needed]
 
-#### Hardware
+## Citation
 
-[More Information Needed]
+```bibtex
+@online{Depaligemma,
+  AUTHOR = {Loïc SOKOUDJOU SONAGU and Yoann SOLA},
+  URL = {https://huggingface.co/cmarkea/paligemma-3b-ft-docvqa-896-lora},
+  YEAR = {2024},
+  KEYWORDS = {Multimodal ; VQA},
+}
 
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]
-### Framework versions
+Find the base model paper [here](https://arxiv.org/abs/2407.07726).
 
 - PEFT 0.11.1