Update README.md

README.md

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-library_name: transformers
-tags: []
+datasets:
+- Norquinal/claude_multiround_chat_1k
+license: cc-by-nc-4.0
 ---
+This is [Jamba-v0.1](https://huggingface.co/ai21labs/Jamba-v0.1) fine-tuned using QLoRA (4-bit precision) on my [claude_multiround_chat_1k](https://huggingface.co/datasets/Norquinal/claude_multiround_chat_1k) dataset, which is a randomized subset of ~1000 samples from my [claude_multiround_chat_30k](https://huggingface.co/datasets/Norquinal/claude_multiround_chat_30k) dataset.
 
-# Model Card for Model ID
+## Prompt Format
+The model was finetuned with the a pseudo-Alpaca format:
+```
+### Instruction
+A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.
 
-<!-- Provide a quick summary of what the model is/does. -->
+### Input
+{instruction}
 
+### Response
 
+```
 
-## Model Details
+## Example Usage
+### Instruction
+A chat between a curious user and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the user's questions.
 
-### Model Description
+### Input
+First, give a brief overview of Chinese cuisine, including its regional diversity. next, describe the importance of the five flavors in Chinese cooking. Then, mention three popular Chinese dishes and their main ingredients. After that, provide a popular Chinese cooking technique and an example of a dish prepared using that technique. Finally, discuss the role of tea in traditional Chinese culture.
 
-<!-- Provide a longer summary of what this model is. -->
+### Response
+>Chinese cuisine is incredibly diverse due to China's vast size and long history. Different regions have developed distinct styles based on local climates, agriculture, and cultural influences. Northern Chinese food tends to be heartier with more wheat-based dishes like dumplings and noodles while southern Chinese cuisine features more rice-based meals with seafood from nearby rivers and coastlines. 
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+>The Five Flavors - sour, sweet, bitter, salty, and umami (savory) - are foundational principles of balance and harmony in Chinese cooking. Chefs aim to incorporate all five flavors into each meal through a combination of different seasonings, sauces, and techniques. This creates well-rounded dishes that satisfy multiple taste preferences.   
 
-- **Developed by:** [More Information Needed]
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-- **Finetuned from model [optional]:** [More Information Needed]
+>Some popular Chinese dishes include:  
+>• Kung Pao Chicken made with chicken breast, peanuts, chili peppers, and Sichuan peppercorns in a savory sauce
+>• Mapo Tofu featuring soft tofu cubes cooked in a spicy sauce with minced pork or beef, fermented black beans, garlic, ginger, and scallions    
+>• Hot Pot consisting of thinly sliced meat and vegetables boiled at the table in flavored broth served with dipping sauces
 
-### Model Sources [optional]
+>Steaming is one common Chinese cooking technique used for both meats and vegetables. Steamed Fish with Ginger and Scallions exemplifies this method where fish fillets are steamed atop chopped ginger slices and green onions until fully cooked yet still tender.     
 
-<!-- Provide the basic links for the model. -->
+>Tea plays an integral part in Chinese culture dating back thousands of years. It is consumed daily as a beverage but also valued for medicinal properties and ceremonial purposes associated with hospitality, etiquette, and spirituality. Tea houses remain popular social gathering places throughout modern China.
 
-- **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. -->
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-[More Information Needed]
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-### 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]
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-### Out-of-Scope Use
-
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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-[More Information Needed]
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-## Bias, Risks, and Limitations
-
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
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-### 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. -->
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-#### 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 -->
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-#### 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]
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-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
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-[More Information Needed]
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-#### Metrics
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-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
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-[More Information Needed]
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-### Results
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-[More Information Needed]
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-#### Summary
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-
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-## Model Examination [optional]
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-<!-- 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]
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-## Technical Specifications [optional]
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-### Model Architecture and Objective
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-[More Information Needed]
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-### Compute Infrastructure
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-[More Information Needed]
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-#### Hardware
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-[More Information Needed]
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-#### Software
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-[More Information Needed]
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-## 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. -->
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-**BibTeX:**
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-[More Information Needed]
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-**APA:**
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-[More Information Needed]
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-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
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-[More Information Needed]
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-## More Information [optional]
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-## Model Card Authors [optional]
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-[More Information Needed]
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-## Model Card Contact
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-[More Information Needed]
+>Hope this provides a good summary covering key aspects of Chinese cuisine you requested! I tried to organize my response logically starting broadly then narrowing down specific examples.