Duplicate from vanta-research/atom-80b

Co-authored-by: Tyler <unmodeled-tyler@users.noreply.huggingface.co>

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README.md

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+---
+license: apache-2.0
+language:
+- en
+base_model:
+- Qwen/Qwen3-Next-80B-A3B-Instruct
+base_model_relation: finetune
+library_name: transformers
+tags:
+- qwen3
+- qwen3-next
+- qwen
+- vanta-research
+- cognitive-configuration
+- text-generation
+- instruction-following
+- cognitive-ai
+- friendly-ai
+- helpful-ai
+- persona-ai
+- philosophical
+- emotional-intelligence
+- atom
+- collaborative-ai
+- collaboration
+- conversational-ai
+- conversational
+- alignment
+- chat
+- chatbot
+- reasoning
+- friendly
+---
+
+<div align="center">
+
+![vanta_trimmed](https://cdn-uploads.huggingface.co/production/uploads/686c460ba3fc457ad14ab6f8/hcGtMtCIizEZG_OuCvfac.png)
+  
+  <h1>VANTA Research</h1>
+    
+  <p><strong>Independent AI research lab building safe, resilient language models optimized for human-AI collaboration</strong></p>
+  
+  <p>
+    <a href="https://vantaresearch.xyz"><img src="https://img.shields.io/badge/Website-vantaresearch.xyz-black" alt="Website"/></a>
+    <a href="https://merch.vantaresearch.xyz"><img src="https://img.shields.io/badge/Merch-merch.vantaresearch.xyz-sage" alt="Merch"/></a>
+    <a href="https://x.com/vanta_research"><img src="https://img.shields.io/badge/@vanta_research-1DA1F2?logo=x" alt="X"/></a>
+    <a href="https://github.com/vanta-research"><img src="https://img.shields.io/badge/GitHub-vanta--research-181717?logo=github" alt="GitHub"/></a>
+  </p>
+</div>
+
+
+---
+# Atom-80B
+
+## Overview
+
+Atom-80B is a state-of-the-art language model fine-tuned on the Qwen3 80B Next base, optimized for high-fidelity reasoning, collaborative interaction, and cognitive extension. Atom-80B is designed to be friendly, enthusiastic, and collaboration-first. 
+
+This model is a continuation of Project Atom from VANTA Research, which aims to scale the Atom persona from 4B-400B+. This model is the 5th in the Project Atom series.
+
+Key strengths:
+- Complex, multi-step reasoning
+- Collaborative task execution and agentic workflows
+- Stable, flavorful persona alignment
+- Optimized inference efficiency
+
+---
+
+## Training and Data
+
+### Base Model
+- **Qwen3 80B Next**: A leading foundation model with robust multilingual and coding capabilities.
+
+### Fine-Tuning Datasets
+Atom-80B was fine-tuned on the same high-quality datasets as the smaller Atom variants, including:
+- Collaborative exploration and brainstorming
+- Research synthesis and question formulation
+- Technical explanation at varying complexity levels
+- Lateral thinking and creative problem-solving
+- Empathetic and supportive dialogue patterns
+
+## Intended Use
+
+### Primary Applications
+
+- **Collaborative Brainstorming:** Generating diverse ideas and building iteratively on user suggestions
+- **Research Assistance:** Synthesizing information, identifying key arguments, and formulating research questions
+- **Technical Explanation:** Simplifying complex concepts across difficulty levels (including ELI5)
+- **Code Discussion:** Exploring implementation approaches, debugging strategies, and architectural decisions
+- **Creative Problem-Solving:** Encouraging unconventional approaches and lateral thinking
+
+### Out-of-Scope Use
+
+This model shall not be used for:
+- High-stakes decision-making without human oversight
+- Medical, legal, or financial advice
+- Generation of harmful, biased, or misleading content
+- Applications requiring guaranteed factual accuracy
+
+## Usage
+
+### Installation
+```
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained("vanta-research/atom-80B", torch_dtype="auto")
+tokenizer = AutoTokenizer.from_pretrained("vanta-research/atom-80B")
+inputs = tokenizer("Explain quantum computing like I'm 10.", return_tensors="pt").to("cuda")
+outputs = model.generate(**inputs, max_new_tokens=256)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+## Ethical Considerations
+
+This model is designed to support exploration and learning, not to replace human judgment. Users should:
+
+- Verify factual claims against authoritative sources
+- Apply critical thinking to generated suggestions
+- Recognize the model's limitations in high-stakes scenarios
+- Be mindful of potential biases in outputs
+- Use responsibly in accordance with applicable laws and regulations
+
+## Citation
+
+```bibtex
+@misc{atom-80b,
+  title={Atom-80B: A Collaborative Thought Partner},
+  author={VANTA Research},
+  year={2026},
+  howpublished={https://huggingface.co/vanta-research/atom-80b}
+}
+```
+
+
+## Contact
+
+- Organization: hello@vantaresearch.xyz
+- Engineering/Design: tyler@vantaresearch.xyz

added_tokens.json

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0].role == 'system' %}
+        {{- messages[0].content + '\n\n' }}
+    {%- endif %}
+    {{- "# 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>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\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" }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if message.content is string %}
+        {%- set content = message.content %}
+    {%- else %}
+        {%- set content = '' %}
+    {%- endif %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- if message.tool_calls %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if (loop.first and content) or (not loop.first) %}
+                    {{- '\n' }}
+                {%- endif %}
+                {%- if tool_call.function %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {{- '<tool_call>\n{"name": "' }}
+                {{- tool_call.name }}
+                {{- '", "arguments": ' }}
+                {%- if tool_call.arguments is string %}
+                    {{- tool_call.arguments }}
+                {%- else %}
+                    {{- tool_call.arguments | tojson }}
+                {%- endif %}
+                {{- '}\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

config.json

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+{
+  "architectures": [
+    "Qwen3NextForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
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+  "decoder_sparse_step": 1,
+  "dtype": "bfloat16",
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+  "full_attention_interval": 4,
+  "head_dim": 256,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 5120,
+  "layer_types": [
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+    "linear_attention",
+    "linear_attention",
+    "full_attention",
+    "linear_attention",
+    "linear_attention",
+    "linear_attention",
+    "full_attention",
+    "linear_attention",
+    "linear_attention",
+    "linear_attention",
+    "full_attention",
+    "linear_attention",
+    "linear_attention",
+    "linear_attention",
+    "full_attention",
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+    "linear_attention",
+    "linear_attention",
+    "full_attention",
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+    "linear_attention",
+    "full_attention",
+    "linear_attention",
+    "linear_attention",
+    "linear_attention",
+    "full_attention",
+    "linear_attention",
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+    "linear_attention",
+    "full_attention",
+    "linear_attention",
+    "linear_attention",
+    "linear_attention",
+    "full_attention",
+    "linear_attention",
+    "linear_attention",
+    "linear_attention",
+    "full_attention",
+    "linear_attention",
+    "linear_attention",
+    "linear_attention",
+    "full_attention",
+    "linear_attention",
+    "linear_attention",
+    "linear_attention",
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+  "linear_conv_kernel_dim": 4,
+  "linear_key_head_dim": 128,
+  "linear_num_key_heads": 16,
+  "linear_num_value_heads": 32,
+  "linear_value_head_dim": 128,
+  "max_position_embeddings": 262144,
+  "mlp_only_layers": [],
+  "model_type": "qwen3_next",
+  "moe_intermediate_size": 512,
+  "norm_topk_prob": true,
+  "num_attention_heads": 16,
+  "num_experts": 512,
+  "num_experts_per_tok": 10,
+  "num_hidden_layers": 48,
+  "num_key_value_heads": 2,
+  "output_router_logits": false,
+  "partial_rotary_factor": 0.25,
+  "rms_norm_eps": 1e-06,
+  "rope_scaling": null,
+  "rope_theta": 10000000,
+  "router_aux_loss_coef": 0.001,
+  "shared_expert_intermediate_size": 512,
+  "tie_word_embeddings": false,
+  "transformers_version": "4.57.3",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

generation_config.json

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+  "temperature": 0.7,
+  "top_k": 20,
+  "top_p": 0.8,
+  "transformers_version": "4.57.3"
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