J.A.R.V.I.S.: Initial!

Hello world!
Finally, I open myself to the public.
Even if its just a small version. xD

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LICENSE

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README.md

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+---
+library_name: transformers
+license: apache-2.0
+license_link: https://huggingface.co/hadadrjt/JARVIS/blob/main/LICENSE
+base_model:
+- Qwen/Qwen3-4B
+tags:
+- jarvis
+- trl
+- sft
+language:
+- en
+---
+
+**J.A.R.V.I.S.**, which stands for "**Just a Rather Very Intelligent System**", is an advanced AI language model inspired by [Iron Man](https://wikipedia.org/wiki/J.A.R.V.I.S.) iconic assistant. This model delivers context-aware, high-fidelity natural language processing capabilities for a wide range of applications.
+
+<div style="font-size: x-small; font-weight: bold;">NOTICE! This is only the base model and a lighter version for public release. To use the more advanced version, please use the available space provided.</div>
+
+## Model Highlights
+
+-  **Powerful Text Generation Engine**  
+**J.A.R.V.I.S.** serves as the core of an AI solution capable of producing natural and creative text with high quality, ready to help you create inspiring and engaging content.
+
+-  **Seamless Integration, Limitless Possibilities**  
+Designed with high flexibility, **J.A.R.V.I.S.** can be easily integrated into various platforms and systems you use, from web applications, chatbots, to automated workflows, adapting to the available resource capacity.
+
+-  **Scalable & Resource-Aware**  
+Regardless of your computing environment, **J.A.R.V.I.S.** can be optimized for optimal performance, from lightweight devices to enterprise-class infrastructure, ensuring efficiency and responsiveness without compromise.
+
+-  **Versatile Use Cases**  
+Ideal for a wide range of needs, from creative content creation, writing assistance, to developing interactive text-based applications, giving you unlimited freedom to innovate.
+
+**J.A.R.V.I.S.** is not just an AI model, it is an intelligent partner ready to transform your ideas into words with a touch of intelligence and high flexibility.
+
+For more detailed information about this model, you can explore all its advantages by referring to the explanation of the underlying base model. [Here](https://huggingface.co/Qwen/Qwen3-4B#qwen3-highlights)!
+
+## Core Capabilities
+
+Discover the amazing power of **J.A.R.V.I.S.**, as your smart and reliable AI companion. It answers your toughest questions with confidence, explains complex ideas in simple terms, translates languages smoothly, writes clean and efficient code, summarizes lengthy information into easy-to-understand points, sparks your creativity with fresh and original content, and guides you through study or research with expert advice. This is only the beginning of what **J.A.R.V.I.S.** can do for you.
+
+## Quick Start
+
+If you have limited resources, don’t be discouraged. You can run this model for free using [Google Colab](https://colab.research.google.com/drive/1FvP9d82cvzu_OrT8HmEGJntU-WDq-63M) or [Kaggle](https://www.kaggle.com/code/hadadrjt/j-a-r-v-i-s). Thanks to both platforms for their valuable resources!
+
+For local use please download this model using the following script guide:
+
+```bash
+# Setup, select one!
+
+# Universal
+pip install torch transformers accelerate safetensors --upgrade
+
+# CPU, if you don’t have a GPU
+pip install torch --index-url https://download.pytorch.org/whl/cpu
+pip install transformers accelerate safetensors --upgrade
+```
+
+```python
+# Script for running this model!
+
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer, TextStreamer
+
+# Model
+model = "hadadrjt/JARVIS"
+
+# Load tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained(model)
+model = AutoModelForCausalLM.from_pretrained(
+    model,
+    torch_dtype="auto",
+    device_map="auto"
+)
+
+# User input
+input = "Tell me about yourself" # Insert your message here.
+
+# Build chat-style prompt
+messages = [{"role": "user", "content": input}]
+
+text = tokenizer.apply_chat_template(
+    messages,
+    tokenize=False,
+    add_generation_prompt=True,
+    enable_thinking=True
+)
+
+# Tokenize input
+model_inputs = tokenizer([text], return_tensors="pt").to(model.device)
+
+# Streaming setup
+streamer = TextStreamer(tokenizer, skip_prompt=True, skip_special_tokens=True)
+
+# Generate response with streaming
+with torch.inference_mode():
+    generated_ids = model.generate(
+        **model_inputs,
+        max_new_tokens=32768,
+        temperature=0.6,
+        top_p=0.95,
+        min_p=0,
+        top_k=20,
+        repetition_penalty=1.0,
+        streamer=streamer
+    )
+```
+
+## Responsible Use
+
+Although **J.A.R.V.I.S.** delivers impressive results, it may reflect biases from its training data and occasionally produce incorrect outputs. It is not intended for real-time safety-critical applications without human oversight. I recommend implementing human review workflows, monitoring outputs for fairness and accuracy, and updating the model with domain-specific data over time.
+
+## Acknowledgments and Contact
+
+This work builds upon the [Qwen3-4B](https://huggingface.co/Qwen/Qwen3-4B) open-source foundation. For feedback, collaboration or support, please reach out to [Hadad Darajat](https://linkedin.com/in/hadadrjt) at [[email protected]](mailto:[email protected]). I welcome contributions that help **J.A.R.V.I.S.** continue to evolve.
+
+Thank you for choosing **J.A.R.V.I.S.** to power your intelligent language applications.

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config.json

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+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
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+  "hidden_act": "silu",
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+  "initializer_range": 0.02,
+  "intermediate_size": 9728,
+  "max_position_embeddings": 40960,
+  "max_window_layers": 36,
+  "model_type": "qwen3",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 36,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 1000000,
+  "sliding_window": null,
+  "tie_word_embeddings": true,
+  "torch_dtype": "float16",
+  "transformers_version": "4.51.3",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

generation_config.json

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+  "transformers_version": "4.51.3"
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+  "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {{- messages[0].content + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n    {%- set index = (messages|length - 1) - loop.index0 %}\n    {%- if ns.multi_step_tool and message.role == \"user\" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}\n        {%- set ns.multi_step_tool = false %}\n        {%- set ns.last_query_index = index %}\n    {%- endif %}\n{%- endfor %}\n{%- for message in messages %}\n    {%- if message.content is string %}\n        {%- set content = message.content %}\n    {%- else %}\n        {%- set content = '' %}\n    {%- endif %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {%- set reasoning_content = '' %}\n        {%- if message.reasoning_content is string %}\n            {%- set reasoning_content = message.reasoning_content %}\n        {%- else %}\n            {%- if '</think>' in content %}\n                {%- set reasoning_content = content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n                {%- set content = content.split('</think>')[-1].lstrip('\\n') %}\n            {%- endif %}\n        {%- endif %}\n        {%- if loop.index0 > ns.last_query_index %}\n            {%- if loop.last or (not loop.last and reasoning_content) %}\n                {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content.strip('\\n') + '\\n</think>\\n\\n' + content.lstrip('\\n') }}\n            {%- else %}\n                {{- '<|im_start|>' + message.role + '\\n' + content }}\n            {%- endif %}\n        {%- else %}\n            {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- endif %}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n    {%- if enable_thinking is defined and enable_thinking is false %}\n        {{- '<think>\\n\\n</think>\\n\\n' }}\n    {%- endif %}\n{%- endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 40960,
+  "pad_token": "<|endoftext|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}