Update README.md

README.md

@@ -1,199 +1,129 @@
 ---
 library_name: transformers
-tags: []
+license: mit
+datasets:
+- chenghao/sec-material-contracts-qa
+- jordyvl/DUDE_subset_100val
+language:
+- en
+pipeline_tag: document-question-answering
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
+# Idefices2-EDGAR
 
+Idefices2 8B fine-tuned on 800+ multi-page documents for Visual DocQA. 
 
 ## Model Details
 
 ### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
-
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
-
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
-
-### Model Sources [optional]
-
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
+Finetuned form [Idefics2](https://huggingface.co/docs/transformers/main/en/model_doc/idefics2).
 
 ## 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. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
-
-### Recommendations
-
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
-
-## How to Get Started with the Model
-
-Use the code below to get started with the model.
-
-[More Information Needed]
+```python
+import torch
+from transformers import AutoProcessor, Idefics2ForConditionalGeneration, BitsAndBytesConfig
+from datasets import load_from_disk
+
+base_model = "HuggingFaceM4/idefics2-8b"
+peft_model_id = "chenghao/idefics2-edgar"
+quantization_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_quant_type="nf4",
+    bnb_4bit_use_double_quant=True,
+    bnb_4bit_compute_dtype=torch.float16
+)
+model = Idefics2ForConditionalGeneration.from_pretrained(
+    peft_model_id,
+    torch_dtype=torch.float16,
+    quantization_config=quantization_config,
+)
+
+model.eval()
+processor = AutoProcessor.from_pretrained(base_model, do_image_splitting=True,
+                                          size={"longest_edge": 490, "shortest_edge": 350})
+dataset = load_from_disk("local-dataset")
+test_example = dataset["test"][30]
+images, question, answer = test_example["images"], test_example["question"], test_example["answer"]
+
+messages = [
+    {
+        "role": "user",
+        "content": [{"type": "image"} for _ in range(len(images))] + [{"type": "text", "text": question}],
+    },
+]
+prompt = processor.apply_chat_template(messages, add_generation_prompt=True)
+inputs = processor(text=prompt, images=images, return_tensors="pt").to("cuda")
+with torch.no_grad():
+    generated_ids = model.generate(**inputs, max_new_tokens=1024)
+generated_texts = processor.batch_decode(generated_ids, skip_special_tokens=True)
+preds = [t.split("Assistant:", 1)[-1].strip() for t in generated_texts]
+print(f"""
+Question: {question}
+Answer: {answer}
+Prediction: {preds or 'N/A'}
+""")
+```
 
 ## 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]
+[SEC Contract QA](https://huggingface.co/datasets/chenghao/sec-material-contracts-qa)
 
 ### Training Procedure
 
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+10 epochs with QLoRA.
 
 #### Preprocessing [optional]
 
-[More Information Needed]
+No image splitting due to memory limit.
+
+```python
+processor = AutoProcessor.from_pretrained(
+    "HuggingFaceM4/idefics2-8b",
+    do_image_splitting=False,
+    size={"longest_edge": 490, "shortest_edge": 350}
+)
+```
 
 
 #### 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 -->
+```python
+quantization_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_quant_type="nf4",
+    bnb_4bit_use_double_quant=True,
+    bnb_4bit_compute_dtype=torch.float16
+)
+model = Idefics2ForConditionalGeneration.from_pretrained(
+    "HuggingFaceM4/idefics2-8b",
+    torch_dtype=torch.float16,
+    quantization_config=quantization_config,
+)
+```
 
 #### 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. -->
+TODO
 
 ### 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]
+TODO
 
 #### Metrics
 
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
+TODO
 
 ### Results
 
-[More Information Needed]
+TODO
 
 #### 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
-
-[More Information Needed]
-
-#### 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]