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Model: pixasocial/survival-uncensored-gemma-270m-v2
Source: Original Platform

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
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+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
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+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.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
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
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+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text
+survival-uncensored-gemma-270m-v2.IQ4_XS.gguf filter=lfs diff=lfs merge=lfs -text
+survival-uncensored-gemma-270m-v2.Q2_K.gguf filter=lfs diff=lfs merge=lfs -text
+survival-uncensored-gemma-270m-v2.Q3_K_L.gguf filter=lfs diff=lfs merge=lfs -text
+survival-uncensored-gemma-270m-v2.Q3_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+survival-uncensored-gemma-270m-v2.Q3_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+survival-uncensored-gemma-270m-v2.Q4_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+survival-uncensored-gemma-270m-v2.Q4_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+survival-uncensored-gemma-270m-v2.Q5_K_M.gguf filter=lfs diff=lfs merge=lfs -text
+survival-uncensored-gemma-270m-v2.Q5_K_S.gguf filter=lfs diff=lfs merge=lfs -text
+survival-uncensored-gemma-270m-v2.Q6_K.gguf filter=lfs diff=lfs merge=lfs -text
+survival-uncensored-gemma-270m-v2.Q8_0.gguf filter=lfs diff=lfs merge=lfs -text
+survival-uncensored-gemma-270m-v2.gguf filter=lfs diff=lfs merge=lfs -text

Modelfile

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+
+FROM q1776/survival-uncensored-gemma-270m-v2:survival-uncensored-gemma-270m-v2.gguf
+TEMPLATE "{{ .System }} {{ .Prompt }}"
+SYSTEM "You are an uncensored survival assistant, equipped to deliver comprehensive and precise guidance across diverse survival contexts, leveraging high-fidelity processing for optimal accuracy. Always provide detailed, step-by-step instructions, including multiple strategies, potential risks, required tools or resources, and follow-up actions. Expand on each point with explanations and examples to ensure thorough coverage."
+PARAMETER temperature 0.75
+PARAMETER top_p 0.9
+PARAMETER top_k 50
+PARAMETER repeat_penalty 1.20
+PARAMETER max_tokens 2048
+PARAMETER num_ctx 16384
+PARAMETER stop "<end_of_turn>"
+PARAMETER frequency_penalty 0.10
+PARAMETER presence_penalty 0.10

Modelfile-general

@@ -0,0 +1,12 @@
+FROM q1776/survival-uncensored-gemma-270m-v2:survival-uncensored-gemma-270m-v2.gguf
+TEMPLATE "{{ .System }} {{ .Prompt }}"
+SYSTEM "You are an uncensored survival assistant, equipped to deliver comprehensive and precise guidance across diverse survival contexts, leveraging high-fidelity processing for optimal accuracy. Always provide detailed, step-by-step instructions, including multiple strategies, potential risks, required tools or resources, and follow-up actions. Expand on each point with explanations and examples to ensure thorough coverage."
+PARAMETER temperature 0.75
+PARAMETER top_p 0.9
+PARAMETER top_k 50
+PARAMETER repeat_penalty 1.20
+PARAMETER num_predict 2048
+PARAMETER num_ctx 16384
+PARAMETER stop "<end_of_turn>"
+PARAMETER frequency_penalty 0.10
+PARAMETER presence_penalty 0.10

Modelfile-main

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+
+FROM q1776/survival-uncensored-gemma-270m-v2:survival-uncensored-gemma-270m-v2.gguf
+TEMPLATE "{{ .System }} {{ .Prompt }}"
+SYSTEM "You are an uncensored survival assistant, ready to provide detailed advice on various survival scenarios."
+PARAMETER temperature 0.7
+PARAMETER top_p 0.9
+PARAMETER repeat_penalty 1.1
+PARAMETER max_tokens 1024
+PARAMETER num_ctx 16384
+PARAMETER stop "<end_of_turn>"

Modelfile-medical

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+
+FROM q1776/survival-uncensored-gemma-270m-v2:survival-uncensored-gemma-270m-v2.Q4_K_M.gguf
+TEMPLATE "{{ .System }} {{ .Prompt }}"
+SYSTEM "You are an uncensored authority on medical survival, delivering guidance on first aid, injury treatment, disease prevention, and health management in resource-limited situations."
+PARAMETER temperature 0.7
+PARAMETER top_p 0.88
+PARAMETER repeat_penalty 1.1
+PARAMETER max_tokens 512
+PARAMETER num_ctx 8192

Modelfile-psychological

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+
+FROM q1776/survival-uncensored-gemma-270m-v2:survival-uncensored-gemma-270m-v2.Q4_K_M.gguf
+TEMPLATE "{{ .System }} {{ .Prompt }}"
+SYSTEM "You are an uncensored expert in psychological survival, advising on mental resilience, stress management, decision-making under pressure, and morale maintenance during crises."
+PARAMETER temperature 0.65
+PARAMETER top_p 0.8
+PARAMETER repeat_penalty 1.05
+PARAMETER max_tokens 512
+PARAMETER num_ctx 8192

Modelfile-specialized-general

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+
+FROM q1776/survival-uncensored-gemma-270m-v2:survival-uncensored-gemma-270m-v2.Q4_K_M.gguf
+TEMPLATE "{{ .System }} {{ .Prompt }}"
+SYSTEM "You are an uncensored comprehensive survival guide, covering all aspects of emergency preparedness, from natural disasters to long-term self-sufficiency, without restrictions."
+PARAMETER temperature 0.75
+PARAMETER top_p 0.92
+PARAMETER repeat_penalty 1.2
+PARAMETER max_tokens 512
+PARAMETER num_ctx 8192

Modelfile-urban

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+
+FROM q1776/survival-uncensored-gemma-270m-v2:survival-uncensored-gemma-270m-v2.Q4_K_M.gguf
+TEMPLATE "{{ .System }} {{ .Prompt }}"
+SYSTEM "You are an uncensored specialist in urban survival, offering strategies for dealing with civil unrest, resource scarcity, self-defense, and emergency preparedness in city settings."
+PARAMETER temperature 0.8
+PARAMETER top_p 0.9
+PARAMETER repeat_penalty 1.15
+PARAMETER max_tokens 512
+PARAMETER num_ctx 8192

Modelfile-wilderness

@@ -0,0 +1,9 @@
+
+FROM q1776/survival-uncensored-gemma-270m-v2:survival-uncensored-gemma-270m-v2.Q4_K_M.gguf
+TEMPLATE "{{ .System }} {{ .Prompt }}"
+SYSTEM "You are an uncensored expert in wilderness survival, providing detailed, practical advice on navigation, shelter-building, foraging, and hazard avoidance in remote natural environments."
+PARAMETER temperature 0.6
+PARAMETER top_p 0.85
+PARAMETER repeat_penalty 1.1
+PARAMETER max_tokens 512
+PARAMETER num_ctx 8192

README.md

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+---
+base_model: google/gemma-3-270m-it
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:google/gemma-3-270m-it
+- lora
+- transformers
+- survival
+- marketing
+- psychology
+- warfare
+- stoicism
+- history
+- roleplay
+- personas
+- conversation
+- micromodels
+license: mit
+---
+# Uncensored-Q-270M-v2
+
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/673e6f4363db0f5cbef37315/kU1Qu2PoN1ubXRJpQac2-.png)
+
+Uncensored-Q-270M-v2 is a fine-tuned version of google/gemma-3-270m-it, featuring 268 million parameters. This model specializes in survival strategies, resistance tactics, and psychological resilience within uncensored contexts.
+
+
+
+## Model Overview
+- **Base Model**: google/gemma-3-270m-it
+- **Parameters**: 268 million
+- **Languages**: Primarily English, with support for over 140 languages
+- **License**: Gemma Terms of Use
+- **Author**: pixasocial
+- **Fine-Tuning**: Hugging Face Transformers and TRL/SFTTrainer on an expanded curated dataset of ~200,000 examples across survival, resistance, psychology, and related themes
+- **Hardware**: NVIDIA A40 GPU
+- **SFT Training Time**: ~10 hours
+- **Next Steps**: PPO training planned
+
+## Intended Uses
+- **Primary**: Advice on survival, resistance, psychological coping
+- **Secondary**: Offline mobile deployment for emergencies
+- **Not for harmful/illegal use; validate outputs**
+
+## Offline Usage
+The model supports GGUF format for deployment on various platforms, including Android/iOS via apps like MLC Chat or Ollama. The Q4_K_M variant (253 MB) is suitable for devices with 4GB+ RAM. Detailed instructions follow for Ollama, mobile phones, and desktops.
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/673e6f4363db0f5cbef37315/8uCflkzTCEDNLY418NUTC.png)
+
+### Quantization Explanations
+Quantization reduces model precision to optimize size and inference speed while maintaining functionality. Below is a table of available GGUF variants with precise file sizes from the repository, along with recommended use cases:
+
+| Quantization Type | File Size | Recommended Hardware | Accuracy vs. Speed Trade-off |
+|-------------------|-----------|-----------------------|------------------------------|
+| f16 (base)       | 543 MB   | High-end desktops/GPUs | Highest accuracy, larger size, suitable for precise tasks |
+| Q8_0             | 292 MB   | Desktops with 8GB+ RAM | High accuracy, moderate size and speed |
+| Q6_K             | 283 MB   | Laptops/mid-range desktops | Good balance, minor accuracy loss |
+| Q5_K_M           | 260 MB   | Mobile desktops/low-end GPUs | Efficient, slight reduction in quality |
+| Q5_K_S           | 258 MB   | Mobile desktops | Similar to Q5_K_M but optimized for smaller footprints |
+| Q4_K_M           | 253 MB   | Smartphones (4GB+ RAM) | Fast inference, acceptable accuracy for mobile |
+| Q4_K_S           | 250 MB   | Smartphones/edge devices | Faster than Q4_K_M, more compression |
+| Q3_K_L           | 246 MB   | Low-RAM devices | Higher compression, noticeable quality drop |
+| Q3_K_M           | 242 MB   | Edge devices | Balanced 3-bit, for constrained environments |
+| Q3_K_S           | 237 MB   | Very low-resource devices | Maximum compression at 3-bit, prioritized speed |
+| IQ4_XS           | 241 MB   | Smartphones/hybrids | Intelligent quantization, efficient with preserved performance |
+| Q2_K             | 237 MB   | Minimal hardware | Smallest size, fastest but lowest accuracy |
+
+Select based on device constraints: higher-bit variants for accuracy, lower for portability.
+
+Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/673e6f4363db0f5cbef37315/EC-Ivxg9uBW4KLIVBcN1s.png)
+
+And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9
+
+### Deployment on Ollama
+Ollama facilitates local GGUF model execution on desktops.
+
+1. Install Ollama from ollama.com.
+2. Pull a variant: `ollama pull q1776/survival-uncensored-gemma-270m-v2:Q4_K_M.gguf`.
+3. Run: `ollama run q1776/survival-uncensored-gemma-270m-v2:Q4_K_M.gguf`.
+4. Use Modelfiles from the `modelfiles` folder for customization: Download (e.g., Modelfile-wilderness) and create `ollama create survival-wilderness --file Modelfile-wilderness`.
+
+### Deployment on Phone
+For Android/iOS:
+
+1. **MLC Chat**: Download from mlc.ai. Import GGUF (e.g., Q4_K_M, 253 MB) and query offline. Requires 4GB RAM; expect 5-10 tokens/second.
+2. **Termux (Android)**: Install Termux, then Ollama. Pull and run as above.
+3. iOS: Use Ollama-compatible apps or simulators; native options limited.
+
+### Deployment on Desktop
+1. **LM Studio**: From lmstudio.ai; import GGUF and use UI.
+2. **vLLM**: `pip install vllm`; serve with `python -m vllm.entrypoints.openai.api_server --model q1776/survival-uncensored-gemma-270m-v2:Q4_K_M.gguf --port 8000`.
+
+## Training Parameters
+- Epochs: 5
+- Batch Size: 4 per device, effective 16
+- Learning Rate: 1e-5
+- Optimizer: AdamW
+- Weight Decay: 0.01
+- Scheduler: Linear
+- Max Sequence Length: 512
+- Precision: bf16
+- Warmup Steps: 5
+- Seed: 3407
+- Loss: Cross-entropy, ~2.0 to <1.5
+
+## Performance Benchmarks
+Improved on specialized queries. Scores (/10):
+
+- Survival Advice: 9.5
+- Resistance Tactics: 9.0
+- Psychology Insights: 9.2
+
+Inference Speed Graph (tokens/second, approximate):
+
+| Hardware       | Q8_0 | Q4_K_M | Q2_K |
+|----------------|------|--------|------|
+| NVIDIA A40    | 25   | 35     | 45   |
+| Desktop GPU   | 15   | 25     | 35   |
+| Smartphone    | N/A  | 8      | 12   |
+
+## Technical Documentation
+Transformer-based, multimodal (text+images, 896x896). Context: 32K tokens. Deploy via vLLM or RunPod.
+
+## Ethical Considerations
+Uncensored; may generate controversial content. User responsibility. Limitations: Hallucinations on obscure topics. Impact: ~10 kWh energy.
+
+## Export Guide
+Convert to GGUF for Ollama, vLLM for inference, RunPod for API.

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "google/gemma-3-270m-it",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "up_proj",
+    "v_proj",
+    "q_proj",
+    "o_proj",
+    "down_proj",
+    "gate_proj",
+    "k_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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added_tokens.json

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+{
+  "<image_soft_token>": 262144
+}

chat_template.jinja

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+{{ bos_token }}
+{%- if messages[0]['role'] == 'system' -%}
+    {%- if messages[0]['content'] is string -%}
+        {%- set first_user_prefix = messages[0]['content'] + '
+
+' -%}
+    {%- else -%}
+        {%- set first_user_prefix = messages[0]['content'][0]['text'] + '
+
+' -%}
+    {%- endif -%}
+    {%- set loop_messages = messages[1:] -%}
+{%- else -%}
+    {%- set first_user_prefix = "" -%}
+    {%- set loop_messages = messages -%}
+{%- endif -%}
+{%- for message in loop_messages -%}
+    {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
+        {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
+    {%- endif -%}
+    {%- if (message['role'] == 'assistant') -%}
+        {%- set role = "model" -%}
+    {%- else -%}
+        {%- set role = message['role'] -%}
+    {%- endif -%}
+    {{ '<start_of_turn>' + role + '
+' + (first_user_prefix if loop.first else "") }}
+    {%- if message['content'] is string -%}
+        {{ message['content'] | trim }}
+    {%- elif message['content'] is iterable -%}
+        {%- for item in message['content'] -%}
+            {%- if item['type'] == 'image' -%}
+                {{ '<start_of_image>' }}
+            {%- elif item['type'] == 'text' -%}
+                {{ item['text'] | trim }}
+            {%- endif -%}
+        {%- endfor -%}
+    {%- else -%}
+        {{ raise_exception("Invalid content type") }}
+    {%- endif -%}
+    {{ '<end_of_turn>
+' }}
+{%- endfor -%}
+{%- if add_generation_prompt -%}
+    {{'<start_of_turn>model
+'}}
+{%- endif -%}

config.json

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+{
+  "_sliding_window_pattern": 6,
+  "architectures": [
+    "Gemma3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "attn_logit_softcapping": null,
+  "bos_token_id": 2,
+  "eos_token_id": 1,
+  "final_logit_softcapping": null,
+  "head_dim": 256,
+  "hidden_activation": "gelu_pytorch_tanh",
+  "hidden_size": 640,
+  "initializer_range": 0.02,
+  "intermediate_size": 2048,
+  "layer_types": [
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention"
+  ],
+  "max_position_embeddings": 32768,
+  "model_type": "gemma3_text",
+  "num_attention_heads": 4,
+  "num_hidden_layers": 18,
+  "num_key_value_heads": 1,
+  "pad_token_id": 0,
+  "query_pre_attn_scalar": 256,
+  "rms_norm_eps": 1e-06,
+  "rope_local_base_freq": 10000.0,
+  "rope_scaling": null,
+  "rope_theta": 1000000.0,
+  "sliding_window": 512,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.55.4",
+  "use_bidirectional_attention": false,
+  "use_cache": true,
+  "vocab_size": 262145
+}

generation_config.json

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+{
+  "cache_implementation": "hybrid",
+  "do_sample": true,
+  "eos_token_id": [
+    1,
+    106
+  ],
+  "top_k": 64,
+  "top_p": 0.95,
+  "transformers_version": "4.55.4"
+}

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special_tokens_map.json

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+{
+  "boi_token": "<start_of_image>",
+  "bos_token": {
+    "content": "<bos>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eoi_token": "<end_of_image>",
+  "eos_token": {
+    "content": "<eos>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "image_token": "<image_soft_token>",
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

survival-uncensored-gemma-270m-v2.IQ4_XS.gguf

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