Super-squash branch 'main' using huggingface_hub

Co-authored-by: tetherjan <tetherjan@users.noreply.huggingface.co>

.gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
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+*.pickle filter=lfs diff=lfs merge=lfs -text
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+*.pt filter=lfs diff=lfs merge=lfs -text
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+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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README.md

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+---
+license: apache-2.0
+language:
+- en
+tags:
+- qwen3
+- base-model
+- causal-lm
+- transformer
+- educational
+- STEM
+- megatron
+---
+
+# QVAC Genesis II Pretrained Model - Option-Level Reasoning Prompt
+
+## Key Highlights
+
+* **Pretrained on QVAC Genesis II**  
+This model has been pretrained on Tether’s **QVAC Genesis II** dataset. 
+
+    Dataset card: https://huggingface.co/datasets/qvac/GenesisII
+
+    The checkpoint uses the **Option-Level Reasoning prompt** format and was pretrained on approximately **53B tokens**, using **BF16 mixed precision** and a **4,096-token** context window, with a **Qwen3-family 1.7B-parameter** decoder-only transformer architecture.
+
+* **Checkpoints in Hugging Face format**  
+Checkpoints are provided in standard Hugging Face format for inference, continual pretraining, and fine-tuning.
+
+* **Educational coverage**  
+QVAC Genesis II includes the following domains:
+  - Machine learning
+  - High school statistics
+  - High school chemistry
+  - Econometrics
+  - College chemistry
+  - College physics
+  - Geography
+  - Astronomy
+  - College computer science
+  - Electrical engineering
+  - High school computer science
+
+---
+
+## Intended Uses
+
+* Continual pretraining or fine-tuning for educational applications (STEM tutoring, QA systems, curriculum support)
+* Benchmarking reasoning and subject-specific QA performance
+* Research into synthetic dataset-driven LLM pretraining
+
+---
+
+## Model Details
+
+### Model Description
+
+* **Developed by:** QVAC by Tether
+* **Model type:** Decoder-only Transformer (causal LM)
+* **Language(s) (NLP):** Primarily English
+* **License:** Apache-2.0
+* **Finetuned from model:** None (randomly initialized)
+* **Intended stage:** Base pretrained model (no SFT / RLHF)
+
+### Dataset Details
+
+* **Dataset:** [qvac/GenesisII](https://huggingface.co/datasets/qvac/GenesisII)
+* **Prompt format:** Option-Level Reasoning prompt
+
+---
+
+## Uses
+
+### Direct Use
+
+* General language modeling: next-token prediction, continuation, summarization, drafting.
+* Research baseline for scaling, data ablations, or tokenizer studies.
+
+### Downstream Use (recommended)
+
+* Continued Pre-Training (CPT) on more tokens.
+* SFT for assistants, domain experts, or task-specific models.
+* Preference optimization / RLHF for safer, more helpful behavior.
+* Adapters/LoRA for efficient domain specialization.
+
+### Out-of-Scope Use
+
+* High-stakes decision-making (medical/financial/legal)
+* Safety-critical or autonomous control systems
+* Unfiltered end-user deployment without alignment / safety layers
+* Any use that violates applicable laws or platform policies.
+
+---
+
+## Bias, Risks, and Limitations
+
+* **Bias & toxicity:** May reflect or amplify biases present in web text.
+* **Hallucinations:** Can produce confident but incorrect statements or citations.
+* **Security / privacy:** May emit continuous random strings.
+* **Context limit:** 4,096 tokens; longer inputs require chunking.
+
+### Recommendations
+
+* Disclose limitations to downstream users.
+* Research model: not intended for production use cases.
+
+---
+
+## How to Get Started
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+model_id = "qvac/genesis-ii-model-ol-reasoning"
+
+tok = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype=torch.bfloat16,
+    device_map="auto",
+)
+
+prompt = "Explain the principle of conservation of energy."
+inputs = tok(prompt, return_tensors="pt").to(model.device)
+out = model.generate(**inputs, max_new_tokens=256, do_sample=True, top_p=0.9, temperature=0.7)
+print(tok.decode(out[0], skip_special_tokens=True))
+```
+
+---
+
+## Training Details
+
+### Training Data
+
+* **Dataset:** [qvac/GenesisII](https://huggingface.co/datasets/qvac/GenesisII)
+* **Prompt format:** Option-Level Reasoning prompt
+* **Total pretraining tokens:** ~**53B** tokens
+* **Tokenizer:** Qwen3 tokenizer
+
+### Training Procedure
+
+* **Framework:** Megatron-LM (Megatron-Core)
+* **Sequence length:** 4,096
+* **Precision:** BF16
+* **Optimizer:** AdamW (β₁=0.9, β₂=0.95), weight decay 0.01
+* **Learning rate:** 2e-4 → 2e-5
+* **Warmup:** 607 steps
+* **Training steps:** 6,079
+* **Gradient clipping:** 1.0
+* **Seed:** 42
+* **Logging:** every 100 steps
+* **Checkpointing:** every 500 steps
+
+---
+
+## Multi-Node GPU Setup
+
+* **Cluster:** 8 nodes, each with 8 NVIDIA H100 80GB (64 GPUs total)
+* **Scheduler:** Slurm
+* **Launch:** `srun` + `torchrun`
+* **Framework:** Megatron-LM
+
+---
+
+## Technical Specifications
+
+### Model Architecture and Objective
+
+* **Architecture:** Qwen3-style decoder-only Transformer
+* **Parameters:** ~1.7B
+* **Context length:** 4,096 tokens
+* **Objective:** Causal LM (next-token prediction)
+
+---
+
+## Conversion & Inference
+
+This checkpoint is provided in Hugging Face format for inference with `transformers`.
+
+---
+
+## Changelog
+
+* v0.1 (2025-12-16): Initial release - Option-Level Reasoning prompt variant

added_tokens.json

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+{
+  "</think>": 151668,
+  "</tool_call>": 151658,
+  "</tool_response>": 151666,
+  "<think>": 151667,
+  "<tool_call>": 151657,
+  "<tool_response>": 151665,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
+  "<|fim_prefix|>": 151659,
+  "<|fim_suffix|>": 151661,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644,
+  "<|image_pad|>": 151655,
+  "<|object_ref_end|>": 151647,
+  "<|object_ref_start|>": 151646,
+  "<|quad_end|>": 151651,
+  "<|quad_start|>": 151650,
+  "<|repo_name|>": 151663,
+  "<|video_pad|>": 151656,
+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}

chat_template.jinja

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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 %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
+        {%- set ns.multi_step_tool = false %}
+        {%- set ns.last_query_index = index %}
+    {%- endif %}
+{%- endfor %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set content = message.content %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is defined and message.reasoning_content is not none %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in message.content %}
+                {%- set content = message.content.split('</think>')[-1].lstrip('\n') %}
+                {%- set reasoning_content = message.content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {%- if loop.last or (not loop.last and reasoning_content) %}
+                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
+            {%- else %}
+                {{- '<|im_start|>' + message.role + '\n' + content }}
+            {%- endif %}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- 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' }}
+        {{- message.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' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- endif %}
+{%- endif %}

config.json

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+{
+  "architectures": [
+    "Qwen3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 6144,
+  "layer_types": [
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 32768,
+  "max_window_layers": 28,
+  "model_type": "qwen3",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 28,
+  "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": "bfloat16",
+  "transformers_version": "4.53.3",
+  "use_cache": true,
+  "use_sliding_window": false,
+  "vocab_size": 151936
+}

generation_config.json

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+{
+  "bos_token_id": 151643,
+  "eos_token_id": 151643,
+  "max_new_tokens": 2048,
+  "transformers_version": "4.53.3",
+  "trust_remote_code": true
+}

model.safetensors

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+oid sha256:97a3f0bf70be140f09e9539575e767bc79d706b15bef7201479c7a75f6dd6a33
+size 3441185576

special_tokens_map.json

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+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
+    "<|box_end|>",
+    "<|quad_start|>",
+    "<|quad_end|>",
+    "<|vision_start|>",
+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
+  "eos_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<|endoftext|>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

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+oid sha256:aeb13307a71acd8fe81861d94ad54ab689df773318809eed3cbe794b4492dae4
+size 11422654

tokenizer_config.json

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+  "add_bos_token": false,
+  "add_prefix_space": false,
+  "added_tokens_decoder": {
+    "151643": {
+      "content": "<|endoftext|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151644": {
+      "content": "<|im_start|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151645": {
+      "content": "<|im_end|>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "151646": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
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+      "normalized": false,
+      "rstrip": false,
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+      "special": false
+    },
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+      "rstrip": false,
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+    "<|im_start|>",
+    "<|im_end|>",
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+    "<|box_start|>",
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+    "<|vision_end|>",
+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
+  ],
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+  "clean_up_tokenization_spaces": false,
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+  "errors": "replace",
+  "extra_special_tokens": {},
+  "model_max_length": 131072,
+  "pad_token": "<|endoftext|>",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null
+}