Update README.md

README.md

@@ -1,200 +1,98 @@
 ---
 library_name: transformers
 tags:
-- llama-factory
+- dockerllama
+- docker
+- nlp
+- command-generation
+license: llama3.2
+datasets:
+- MattCoddity/dockerNLcommands
+language:
+- en
+base_model:
+- meta-llama/Llama-3.2-1B
 ---
 
-# Model Card for Model ID
-
-<!-- Provide a quick summary of what the model is/does. -->
-
+# Model Card for DockerLlama
 
+DockerLlama is a Transformers model designed to interpret natural language queries and generate Docker commands. This model facilitates quick and easy command generation for Docker operations, making it ideal for users who want to interact with Docker without memorizing command syntax.
 
 ## 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.
+DockerLlama, developed as a command-generation model, translates user requests into precise Docker commands. It supports use cases like querying the health of containers, creating networks, and managing Docker resources. DockerLlama is particularly useful for DevOps engineers, software developers, and IT professionals working with containerized applications.
 
-- **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]
+- **Developed by:** [rahulvk007](https://www.rahulvk.com)
+- **Model type:** Language Model fine-tuned for Docker command generation
+- **Language(s):** English (NLP for Docker commands)
+- **License:** llama3.2
+- **Finetuned from model:** meta-llama/Llama-3.2-1B
 
-### 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]
+- **Repository:** [DockerLlama on Hugging Face Hub](https://huggingface.co/rahulvk007/dockerllama)
+- **Dataset:** [MattCoddity/dockerNLcommands](https://huggingface.co/datasets/MattCoddity/dockerNLcommands)
 
 ## 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]
+DockerLlama is used directly to translate natural language queries into Docker commands. For example, "Give me a list of running containers that are healthy" would be translated into ```docker ps --filter 'status=running' --filter 'health=healthy'``` command.
 
 ### Out-of-Scope Use
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
-
-[More Information Needed]
+The model is not suited for general natural language tasks unrelated to Docker or for use cases outside of Docker command generation.
 
 ## Bias, Risks, and Limitations
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
-
-[More Information Needed]
+DockerLlama is focused on Docker commands, so its performance on unrelated queries or commands not supported by Docker may produce incorrect or irrelevant responses.
 
 ### 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.
+Users should verify the generated Docker commands before executing them to avoid unintended effects on their Docker environment.
 
 ## 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]
-
-## Evaluation
-
-<!-- This section describes the evaluation protocols and provides the results. -->
-
-### Testing Data, Factors & Metrics
-
-#### Testing Data
+To deploy the model locally, you can use VLLM. Here are some commands:
 
-<!-- This should link to a Dataset Card if possible. -->
+**Command to deploy with VLLM:**
 
-[More Information Needed]
+```bash
+docker run --runtime nvidia --gpus all -p 9000:8000 --ipc=host vllm/vllm-openai:latest --model rahulvk007/dockerllama
+```
 
-#### Factors
+If you have a low-memory machine with an older GPU (like GTX 1650), try this:
 
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+```bash
+docker run --gpus all -p 9000:8000 --ipc=host vllm/vllm-openai:latest --model rahulvk007/dockerllama --dtype=half --max-model-len=512
+```
 
-[More Information Needed]
+### Important Prompt Setup
 
-#### Metrics
+Use the following system prompt to ensure the model translates queries accurately:
 
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+```
+translate this sentence in docker command
+```
 
-[More Information Needed]
+**Example Request:**
 
-### Results
+To interact with the deployed model, make a POST request to `http://localhost:9000/v1/chat/completions` (change the endpoint to your deployment url) with the following payload:
 
-[More Information Needed]
+```json
+{
+    "model": "rahulvk007/dockerllama",
+    "messages": [
+        {"role": "system", "content": "translate this sentence in docker command"},
+        {"role": "user", "content": "Give me a list of running containers that are healthy."}
+    ]
+}
+```
 
-#### 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]
+## Training Details
 
-## Model Card Contact
+### Training Data
 
-[More Information Needed]
+The model was fine-tuned using the dataset [MattCoddity/dockerNLcommands](https://huggingface.co/datasets/MattCoddity/dockerNLcommands), which includes natural language commands and their Docker command equivalents.