Update README.md

README.md

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 ---
 license: mit
+datasets:
+- Locutusque/InstructMix
+language:
+- en
+metrics:
+- bleu
+- perplexity
+pipeline_tag: text-generation
+widget:
+  - text: '<|USER|> Design a Neo4j database and Cypher function snippet to Display Extreme Dental hygiene: Using Mouthwash for Analysis for Beginners. Implement if/else or switch/case statements to handle different conditions related to the Consent. Provide detailed comments explaining your control flow and the reasoning behind each decision. <|ASSISTANT|> '
 ---
+
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+This a fine-tuned version of gpt2 on Locutusque/InstructMix.
+
+## Model Details
+This model performs significantly better than Locutusque/gpt2-conversational-or-qa. Here are the training results:
+
+
+- BLEU - 26
+- Perplexity - 12
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** Locutusque
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** GPT-2
+- **Language(s) (NLP):** English
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** GPT-2
+
+### 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. -->
+This model is designed to follow instructions, or partake in conversations.
+
+### Direct Use
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+Instruction-following or conversational.
+
+### 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.
+
+```python
+import torch
+from transformers import GPT2Tokenizer, GPT2LMHeadModel
+
+tokenizer = GPT2Tokenizer.from_pretrained('gpt2-conversational-retrain')
+model = GPT2LMHeadModel.from_pretrained('gpt2-conversational-retrain')
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+def generate_text(model, tokenizer, prompt, max_length=1024):
+    prompt = f'<|USER|> {prompt} <|ASSISTANT|> '
+    input_ids = tokenizer.encode(prompt, add_special_tokens=True, return_tensors="pt").to(device)
+    attention_mask = torch.ones_like(input_ids).to(device)
+    output = model.generate(input_ids, 
+                            max_length=max_length, 
+                            do_sample=True,
+                            temperature=0.3, 
+                            top_k=23, 
+                            top_p=0.7,
+                            repetition_penalty=1.176,
+                            pad_token_id=tokenizer.pad_token_id,
+                            eos_token_id=tokenizer.eos_token_id,
+                            attention_mask=attention_mask)
+    output_ids = tokenizer.decode(output[0], skip_special_tokens=False)
+    return output_ids
+# Loop to interact with the model
+while True:
+    prompt = input("Enter a prompt (or 'q' to quit): ")
+    if prompt == "q":
+        break
+    output_text = generate_text(model, tokenizer, prompt)
+    print(output_text)
+```
+
+## Training Details
+
+### Training Data
+
+<!-- This should link to a Data 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. -->
+
+https://huggingface.co/datasets/Locutusque/InstructMix
+
+This model has so far been trained on 10% of the linked data, with more training sessions to come.
+
+### 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:** fp16 non-mixed precision <!--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 Data 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
+
+[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]