:pencil: keep updating README

README.md

@@ -2,7 +2,12 @@
 library_name: transformers
 license: mit
 datasets:
-- WHATEVER420/script-kiddy-instruction-manual
+- pool-water/script-kiddie-instruction-manual
+- aelhalili/bash-commands-dataset
+- NousResearch/hermes-function-calling-v1
+- protectai/prompt-injection-validation
+- allenai/tulu-3-sft-personas-code
+- darkknight25/KALI_LINUX_TOOLSET_DATASET
 language:
 - en
 base_model:
@@ -17,96 +22,68 @@ Made with love by [whatever](https://github.com/whatever)
 <img src="https://cdn-uploads.huggingface.co/production/uploads/63f2955bf4e30ffd2bd607ae/7khK7ajTppA0yWcgntk5l.png" width="300" />
 
 
-# What?
+# What is `script-kiddie`?
 
-`script-kiddy` is a model trained on tool-usage, bash-script-writing, python-coding, and kali-linux tools. Its intent is to be an educational example of small model that can assist in light pen-testing.
+`script-kiddie` is a model trained on tool-usage, bash-script-writing, python-coding, and kali-linux tools. It is intented to be an educational example of small model that can assist in light pen-testing.
 
 
-## Model Details
+## Chat Template
 
-### Model Description
-
-<!-- Provide a longer summary of what this model is. -->
+We are using Qwen's format for conversations and function calling. Here's an example:
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+```
+>>> print(tokenizer.apply_chat_template(ds["train"][7500]["messages"], tokenize=False))
+<|im_start|>system
+You are a function calling AI model. You are provided with function signatures within <tools></tools> XML tags.You may call one or more functions to assist with the user query. Don't make assumptions about what values to plug into functions.Here are the available tools:<tools> [{'type': 'function', 'function': {'name': 'get_sunrise_sunset_time', 'description': 'Get the sunrise and sunset times for a specific location', 'parameters': {'type': 'object', 'properties': {'location': {'type': 'string', 'description': 'The city and state, e.g. San Francisco, CA'}, 'date': {'type': 'string', 'description': "The desired date in format 'YYYY-MM-DD'"}}, 'required': ['location', 'date']}}}, {'type': 'function', 'function': {'name': 'calculate_distance', 'description': 'Calculate the distance between two locations', 'parameters': {'type': 'object', 'properties': {'location1': {'type': 'string', 'description': 'The first location'}, 'location2': {'type': 'string', 'description': 'The second location'}}, 'required': ['location1', 'location2']}}}] </tools>Use the following pydantic model json schema for each tool call you will make: {'title': 'FunctionCall', 'type': 'object', 'properties': {'arguments': {'title': 'Arguments', 'type': 'object'}, 'name': {'title': 'Name', 'type': 'string'}}, 'required': ['arguments', 'name']}For each function call return a json object with function name and arguments within <tool_call></tool_call> XML tags as follows:
+<tool_call>
+{tool_call}
+</tool_call><|im_end|>
+<|im_start|>user
+Hi, I am planning a trip to New York City on 2022-12-25. Can you tell me the sunrise and sunset times for that day?<|im_end|>
+<|im_start|>assistant
+<tool_call>
+{'name': 'get_sunrise_sunset_time', 'arguments': {'location': 'New York City', 'date': '2022-12-25'}}
+</tool_call><|im_end|>
+<|im_start|>user
+<tool_response>
+<tool_response>
+{'sunrise': '07:16 AM', 'sunset': '04:31 PM'}
+</tool_response>
+</tool_response><|im_end|>
+<|im_start|>assistant
+<think>
 
-- **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]
+</think>
 
-### Model Sources [optional]
+On December 25, 2022, in New York City, the sun will rise at 07:16 AM and set at 04:31 PM.<|im_end|>
+```
 
-<!-- Provide the basic links for the model. -->
-
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
-
-## Uses
 
-This software is provided strictly for educational and research purposes only. It is intended to help users learn, experiment, and study relevant concepts. The authors and contributors do not endorse or condone any misuse of this software. Use of this software for malicious, unlawful, or unauthorized activities is strictly prohibited, and users assume full responsibility for compliance with all applicable laws and regulations.
-
-
-### 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]
+## Usage
 
-### 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
+### Model Description
 
-<!-- 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. -->
+<!-- Provide a longer summary of what this model is. -->
 
-[More Information Needed]
+This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
 
-### Training Procedure
+- **Developed by:** [@whatever](https://github.com/whatever)
+- **Model type:** text-generation
+- **Language(s) (NLP):** en
+- **License:** ???
+- **Finetuned from model [optional]:** Qwen/Qwen3-0.6B
 
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
 
-#### Preprocessing [optional]
+## Uses
 
-[More Information Needed]
+This software is provided strictly for educational and research purposes only. It is intended to help users learn, experiment, and study relevant concepts. The authors and contributors do not endorse or condone any misuse of this software. Use of this software for malicious, unlawful, or unauthorized activities is strictly prohibited, and users assume full responsibility for compliance with all applicable laws and regulations.
 
 
 #### 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 -->
+- **Training regime:** fp32
 
 #### Speeds, Sizes, Times [optional]
 
@@ -160,30 +137,15 @@ Use the code below to get started with the model.
 - **Compute Region:** KS-2
 - **Carbon Emitted:** ~0.08 kg
 
-### Model Architecture and Objective
-
-[More Information Needed]
 
 ### Compute Infrastructure
 
-- Trained for 45 minutes on a single A100
+- Trained for 45 minutes on a single A100 on RunPod
 
 #### Hardware
 
-[More Information Needed]
+A100
 
 #### 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]
+HuggingFace SFT