Update README.md

README.md

@@ -1,199 +1,95 @@
 ---
 library_name: transformers
-tags: []
+license: cc-by-4.0
+datasets:
+- Johndfm/genrescoh
+language:
+- en
+- zh
+- de
+- it
 ---
 
 # Model Card for Model ID
 
 <!-- Provide a quick summary of what the model is/does. -->
 
+ECoh is a family of transformer-based decoder-only language model finetuned to assess the coherence of responses in dialogue systems. 
 
 
 ## 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]
+### Model Sources
 
 <!-- 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. -->
-
-[More Information Needed]
-
-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
+- **Repository:** https://github.com/johndmendonca/Ecoh
+- **Paper:** https://arxiv.org/abs/2407.11660
 
-### 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]
-
-## 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]
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
-## Evaluation
+# load model
+model_path="Johndfm/ECoh-4B"
+tokenizer = AutoTokenizer.from_pretrained(model_path,padding_side="left")
+base_model = AutoModelForCausalLM.from_pretrained(model_path).to("cuda")
 
-<!-- This section describes the evaluation protocols and provides the results. -->
+# prepare example
+example = "Context:\nA: Dahua's Market . How can I help you ? \nB:  Where is your store located ? \n\nResponse:\nA: Our store is located on 123 Main Street, in the city center."
+messages = [
+      {"role": "system", "content": "You are a Coherence evaluator."}
+      {"role": "user", "content": f"{example}\n\nGiven the context, is the response Coherent (Yes/No)? Explain your reasoning."}
+]
 
-### Testing Data, Factors & Metrics
+text = tokenizer.apply_chat_template(
+        messages,
+        tokenize=False,
+        add_generation_prompt=True
+)
+model_inputs = tokenizer([text], return_tensors="pt").to("cuda")
 
-#### Testing Data
+generated_ids = base_model.generate(
+        model_inputs.input_ids,
+        max_new_tokens=64
+)
 
-<!-- This should link to a Dataset Card if possible. -->
+generated_ids = [
+        output_ids[len(input_ids):] for input_ids, output_ids in zip(model_inputs.input_ids, generated_ids)
+]
 
-[More Information Needed]
+response = tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
+```
 
-#### Factors
+## Training and Evaluation Details
 
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+Please refer to the original paper.
 
-[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
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
+## Citation
 
 <!-- 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]
+```
+@misc{mendonça2024ecoh,
+      title={ECoh: Turn-level Coherence Evaluation for Multilingual Dialogues}, 
+      author={John Mendonça and Isabel Trancoso and Alon Lavie},
+      year={2024},
+      eprint={2407.11660},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2407.11660}, 
+}
+```
 
-[More Information Needed]
 
 ## Model Card Contact
 
-[More Information Needed]
+[email protected]