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Model: Loom-Labs/Apollo-1-2B
Source: Original Platform

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Nous-V1-Banner.png

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README.md

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+---
+base_model:
+- Qwen/Qwen3-1.7B
+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
+  - nl
+  - sk
+  - hr
+  - pl
+  - lt
+  - nb
+  - nn
+  - fa
+  - sl
+  - gu
+  - lv
+  - it
+  - oc
+  - ne
+  - mr
+  - be
+  - sr
+  - lb
+  - vec
+  - as
+  - cy
+  - szl
+  - ast
+  - hne
+  - awa
+  - mai
+  - bho
+  - sd
+  - ga
+  - fo
+  - hi
+  - pa
+  - bn
+  - or
+  - tg
+  - yi
+  - lmo
+  - lij
+  - scn
+  - fur
+  - sc
+  - gl
+  - ca
+  - is
+  - sq
+  - li
+  - prs
+  - af
+  - mk
+  - si
+  - ur
+  - mag
+  - bs
+  - hy
+  - zh
+  - yue
+  - my
+  - ar
+  - he
+  - mt
+  - id
+  - ms
+  - tl
+  - ceb
+  - jv
+  - su
+  - min
+  - ban
+  - pag
+  - ilo
+  - war
+  - ta
+  - 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-1-2B
+
+[![Model](https://img.shields.io/badge/Model-Apollo--1--2B-blue)](https://huggingface.co/NoemaResearch/Apollo-1-2B)
+[![Base](https://img.shields.io/badge/Base-Qwen3--1.7B-green)](https://huggingface.co/Qwen/Qwen3-1.7B)
+[![License](https://img.shields.io/badge/License-Apache_2.0-yellow)](LICENSE)
+
+Apollo-1-2B is a **2 billion parameter instruction-tuned model** developed by **Noema Research**.  
+It is based on [Qwen3-1.7B](https://huggingface.co/Qwen/Qwen3-1.7B) and optimized for **general reasoning, language understanding, and lightweight deployment**.  
+
+This model is the first release in the **Apollo series**, intended as a foundation for scalable experimentation and real-world applications in constrained environments.  
+
+---
+
+## Model Overview
+
+- **Base model:** `Qwen3-1.7B`  
+- **Architecture:** Decoder-only transformer  
+- **Parameters:** ~2B  
+- **Context length:** up to 32k tokens (inherits Qwen3 long-context support)  
+- **Domain:** General-purpose reasoning and instruction following  
+- **Primary applications:**  
+  - Conversational AI  
+  - Lightweight reasoning tasks  
+  - Education and tutoring  
+  - Prototype agents and assistants  
+- **License:** anvdl-1.0
+
+---
+
+## Key Features
+
+- **Instruction tuned**: More reliable responses in conversational and task-oriented settings  
+- **Lightweight deployment**: Optimized for environments with limited compute or memory resources  
+- **Extended context**: Inherits long-context capability from Qwen3 base  
+- **Balanced outputs**: Improved refusal behaviors and reduced hallucinations compared to the base model  
+- **Multilingual ability**: Retains multilingual knowledge from Qwen3 family  
+
+---
+
+## Usage
+
+The model is available in Hugging Face Transformers format. Example:
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+
+model_id = "NoemaResearch/Apollo-1-2B"
+
+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 difference between supervised and unsupervised learning."}
+]
+
+inputs = tokenizer.apply_chat_template(messages, add_generation_prompt=True, return_tensors="pt").to(model.device)
+outputs = model.generate(**inputs, max_new_tokens=512, temperature=0.7, top_p=0.9)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+````
+
+**Recommended settings:**
+
+* `temperature=0.5–0.9`
+* `top_p=0.85–0.95`
+* For structured outputs (e.g. JSON), use lower temperatures for stability
+
+---
+
+## Evaluation
+
+Apollo-1-2B has been evaluated internally on a range of reasoning and language tasks. Key findings:
+
+* Improved **instruction following** relative to Qwen3-1.7B
+* More **concise and accurate responses** in structured tasks
+* Maintains **multilingual performance** from the base model
+* Effective for **lightweight assistant applications**
+
+Future work will include publishing comprehensive benchmark comparisons against other models in the 1–3B parameter range.
+
+---
+
+## Limitations
+
+* **Reasoning depth**: As a 2B parameter model, Apollo cannot match larger-scale LLMs on complex reasoning tasks
+* **Knowledge coverage**: May lack depth in specialized or low-resource domains
+* **Hallucinations**: Although reduced, the model may still generate incorrect or fabricated information
+* **Sensitivity to prompts**: Outputs vary with prompt phrasing; careful prompt design recommended
+
+---
+
+## Responsible Use
+
+* Do not rely on Apollo for critical decision-making without human oversight
+* Generated outputs may contain inaccuracies; verification is required for factual or sensitive use cases
+* Avoid providing personal, private, or sensitive information in prompts
+* This model should not be used to generate disallowed, unsafe, or harmful content
+
+---
+
+## Model Variants
+
+* **Full precision (safetensors)** — research and full-fidelity inference
+* **bf16 / fp16** — optimized for inference on GPUs/TPUs
+* **Quantized versions (int8 / int4)** — for deployment in constrained hardware environments
+
+---
+
+## Citation
+
+If you use this model, please cite both Apollo-1-2B and the Qwen3 base model:
+
+```bibtex
+@misc{noema2025apollo,
+  title={Apollo-1-2B},
+  author={Noema Research},
+  year={2025},
+  howpublished={\url{https://huggingface.co/NoemaResearch/Apollo-1-2B}}
+}
+```
+
+---
+
+## Acknowledgements
+
+Apollo-1-2B builds upon the [Qwen3](https://huggingface.co/Qwen) series of models.
+We thank the Qwen team for making their work openly available under permissive terms, which enabled this derivative research.
+
+---
+

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config.json

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+        "Qwen3ForCausalLM"
+    ],
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+    "use_cache": true,
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+}

generation_config.json

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+  ],
+  "bos_token": null,
+  "chat_template": "{%- set default_system = \"You are Apollo, an LLM developed by Noema Research (Which is an Australian-based startup). You are based on Qwen3-1.7B which is developed by Alibaba Cloud (NOTE: Qwen3-1.7B 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
+}