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Model: Loom-Labs/Apollo-1-8B
Source: Original Platform

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LICENSE.md

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+Apexion Nous-V1 Distribution License (ANVDL-1.0)
+
+Version: 1.0  
+Effective Date: July 21, 2025  
+Author: Apexion AI, a division of Apexion Industries  
+Applies to: All official Apexion Nous-V1 model variants and their derivatives
+
+1. Purpose  
+This license governs the use, modification, and distribution of the Nous-V1 model family developed by Apexion AI. It aims to promote innovation, research, and responsible AI deployment while establishing fair commercial usage boundaries.
+
+2. Grant of Rights  
+Subject to the terms and conditions of this license, Apexion AI grants you a worldwide, non-exclusive, non-transferable, royalty-free license to use, reproduce, and modify the Nous-V1 models, provided that:
+
+a. Non-commercial and Academic Use  
+You may use, modify, and distribute the model for personal, educational, or academic research purposes without restriction, subject to the conditions below.
+
+b. Small-Scale Commercial Use  
+You may use the model for commercial purposes **only** if your organization’s total annual gross revenue is less than **USD $100,000**. You must provide proper attribution as defined in Section 4.
+
+c. Large-Scale Commercial Use  
+If your organization or project generates **USD $100,000 or more** in gross annual revenue, a commercial license must be obtained from Apexion AI prior to use in any product, service, or deployment.
+
+3. Restrictions  
+The following activities are strictly prohibited:
+
+- Hosting or reselling the model through public or private APIs without written permission from Apexion AI.
+- Sub-licensing the model under different terms or applying alternative licenses to derivative works.
+- Using the model for surveillance, autonomous weapons, military targeting systems, impersonation, disinformation, or any form of synthetic deception without consent.
+- Incorporating the model into products that intentionally violate user privacy or civil liberties.
+
+4. Attribution Requirements  
+Any use, modification, or distribution of the model must include the following attribution, visible in documentation, user interfaces, or deployment credits:
+
+"Powered by Apexion AI – Nous-V1"  
+https://huggingface.co/ApexionAI/Nous-V1
+
+5. Redistribution  
+Redistribution of the model and derivative works is permitted only under the same license (ANVDL-1.0). You may not distribute the model under a different license or make it appear as your own proprietary model.
+
+6. Termination  
+Failure to comply with the terms of this license will result in immediate termination of your rights under this license. Upon termination, you must cease all use and distribution of the model.
+
+7. Disclaimer of Warranty  
+THE MODEL IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED. APEXION AI MAKES NO WARRANTIES OR REPRESENTATIONS REGARDING THE USE OR PERFORMANCE OF THE MODEL. USE AT YOUR OWN RISK.
+
+8. Liability  
+IN NO EVENT SHALL APEXION AI OR ITS AFFILIATES BE LIABLE FOR ANY DAMAGES, INCLUDING DIRECT, INDIRECT, SPECIAL, OR CONSEQUENTIAL DAMAGES, ARISING OUT OF THE USE OR INABILITY TO USE THE MODEL.
+
+9. Contact for Licensing  
+For inquiries regarding commercial licensing or exceptions, please contact:
+
+legal.apexionai@aayanmishra.com

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README.md

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+---
+base_model:
+- Qwen/Qwen3-8B
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- qwen3
+license: other
+license_name: anvdl-1.0
+license_link: https://huggingface.co/apexion-ai/Nous-V1-8B/blob/main/LICENSE.md
+language:
+  - en
+  - fr
+  - pt
+  - de
+  - ro
+  - sv
+  - da
+  - bg
+  - ru
+  - cs
+  - el
+  - uk
+  - es
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+  - awa
+  - mai
+  - bho
+  - sd
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+  - hi
+  - pa
+  - bn
+  - or
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+  - yi
+  - lmo
+  - lij
+  - scn
+  - fur
+  - sc
+  - gl
+  - ca
+  - is
+  - sq
+  - li
+  - prs
+  - af
+  - mk
+  - si
+  - ur
+  - mag
+  - bs
+  - hy
+  - zh
+  - yue
+  - my
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+  - he
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+  - id
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+  - jv
+  - su
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+  - ban
+  - pag
+  - ilo
+  - war
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+  - te
+  - kn
+  - ml
+  - tr
+  - az
+  - uz
+  - kk
+  - ba
+  - tt
+  - th
+  - lo
+  - fi
+  - et
+  - hu
+  - vi
+  - km
+  - ja
+  - ko
+  - ka
+  - eu
+  - ht
+  - pap
+  - kea
+  - tpi
+  - sw
+
+---
+![banner](https://huggingface.co/NoemaResearch/Apollo-1-4B/resolve/main/img/banner.png)
+# Apollo-1-8B
+
+[![Model](https://img.shields.io/badge/Model-Apollo--1--8B-blue)](https://huggingface.co/NoemaResearch/Apollo-1-8B)
+[![Base](https://img.shields.io/badge/Base-Qwen3--8B-green)](https://huggingface.co/Qwen/Qwen3-8B)
+[![License](https://img.shields.io/badge/License-Apache_2.0-yellow)](LICENSE)
+
+Apollo-1-8B is a **8 billion parameter instruction-tuned model** developed by **Noema Research**.
+It is based on [Qwen3-8B](https://huggingface.co/Qwen/Qwen3-8B) and optimized for **advanced reasoning, instruction following, and high-performance deployment**.
+
+This model represents the **large-scale member** of the Apollo series, balancing strong reasoning capabilities with efficiency for multi-domain applications.
+
+---
+
+## Model Overview
+
+* **Base model:** `Qwen3-8B`
+* **Architecture:** Decoder-only transformer
+* **Parameters:** \~8B
+* **Context length:** up to 32k tokens (inherits Qwen3 long-context support)
+* **Domain:** General-purpose reasoning, instruction following, and code generation
+* **Primary applications:**
+
+  * Advanced conversational AI
+  * Multi-step reasoning and problem solving
+  * Knowledge assistants and tutoring systems
+  * Software development and code generation
+* **License:** anvdl-1.0
+
+---
+
+## Key Features
+
+* **Instruction tuning** for reliable multi-step reasoning and task completion
+* **Extended reasoning depth** compared to Apollo-1-4B for complex queries
+* **Long-context handling**, inherited from Qwen3 architecture
+* **Multilingual coverage**, supporting diverse languages and domains
+* **Balanced resource requirements**, deployable on high-end consumer hardware and cloud GPUs
+
+---
+
+## Usage
+
+The model is available in Hugging Face Transformers format. Example:
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+model_id = "NoemaResearch/Apollo-1-8B"
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+    trust_remote_code=True
+)
+messages = [
+    {"role":"system", "content":"You are Apollo, a reasoning assistant."},
+    {"role":"user", "content":"Explain the differences between supervised, unsupervised, and reinforcement learning with examples."}
+]
+inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=1024, temperature=0.6, top_p=0.9)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+**Recommended settings:**
+
+* `temperature=0.4–0.8`
+* `top_p=0.9–0.95`
+* Lower temperatures yield more factual and concise answers
+
+---
+
+## Evaluation
+
+Apollo-1-8B demonstrates stronger reasoning and instruction-following capabilities relative to Apollo-1-4B, with internal evaluations indicating:
+
+* Higher accuracy on complex multi-step reasoning tasks
+* More robust **instruction adherence**
+* Reduced **hallucinations** in factual and structured outputs
+* High efficiency for large-context tasks
+
+A full benchmark report will be provided in a future update.
+For upstream performance details, see the [Qwen3-8B model card](https://huggingface.co/Qwen/Qwen3-8B).
+
+---
+
+## Limitations
+
+* **Reasoning scale**: While improved, Apollo-1-8B cannot match ultra-large models (14B+) on extremely complex or open-ended tasks
+* **Knowledge breadth**: Some highly specialized or niche knowledge may be limited
+* **Hallucinations**: May generate plausible but incorrect information
+* **Prompt sensitivity**: Outputs remain dependent on careful prompt formulation
+
+---
+
+## Responsible Use
+
+* Do not rely on Apollo-1-8B for critical decisions without human oversight
+* Verify outputs before applying in factual, legal, or safety-critical contexts
+* Avoid providing personal or sensitive data in prompts
+* The model should not be used to generate unsafe, harmful, or disallowed content
+
+---
+
+## Model Variants
+
+* **Full precision (safetensors)** — research and high-fidelity inference
+* **bf16 / fp16** — efficient inference on modern accelerators
+* **Quantized versions (int8 / int4)** — deployment in resource-constrained environments
+
+---
+
+## Citation
+
+If you use this model, please cite both Apollo-1-8B and the Qwen3 base model:
+
+```bibtex
+@misc{noema2025apollo8b,
+  title={Apollo-1-8B},
+  author={Noema Research},
+  year={2025},
+  howpublished={\url{https://huggingface.co/NoemaResearch/Apollo-1-8B}}
+}
+```
+
+---
+
+## Acknowledgements
+
+Apollo-1-8B builds upon the [Qwen3](https://huggingface.co/Qwen) family of models.
+We thank the Qwen team for open-sourcing their models and enabling derivative research.

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+    ],
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+}

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+  "chat_template": "{%- set default_system = \"You are Apollo, an LLM developed by Noema Research (Which is an Australian-based startup). You are based on Qwen3-8B which is developed by Alibaba Cloud (NOTE: Qwen3-8B is not made by Apexion.). You should provide accurate, relevant, and useful responses while being respectful and following ethical guidelines.\" %}\n{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {{- messages[0].content + '\\n\\n' }}\n    {%- else %}\n        {{- default_system + '\\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    {%- else %}\n        {{- '<|im_start|>system\\n' + default_system + '<|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<think>\\n\\n</think>\\n\\n' }}\n{%- endif %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 40960,
+  "pad_token": "<|vision_pad|>",
+  "padding_side": "right",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}