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Model: YoussefElsafi/PlayerAI-1.2B-v1.5-GGUF Source: Original Platform
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README.md
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README.md
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---
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license: apache-2.0
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language:
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- en
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base_model:
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- LiquidAI/LFM2.5-1.2B-Instruct
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- YoussefElsafi/PlayerAI-1.2B-v1.5
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tags:
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- gguf
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- quantized
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- conversational
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- llama-cpp
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pipeline_tag: text-generation
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---
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**PlayerAI-1.2B-v1.5-GGUF** contains GGUF quantized versions of [PlayerAI-1.2B-v1.5](https://huggingface.co/YoussefElsafi/PlayerAI-1.2B), a fine-tuned conversational language model designed for immersive, human-like interaction in multiplayer social environments.
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This version improves conversational coherence, tone stability, and multi-turn consistency compared to previous releases, while remaining optimized for lightweight local inference.
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---
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## Available Quantizations
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| File | Quant | Size | Quality | Recommended For |
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|------|-------|------|---------|-----------------|
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| `PlayerAI-1.2B-v1.5-Q2_K.gguf` | Q2_K | 483 MB | Lowest | Very limited RAM |
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| `PlayerAI-1.2B-v1.5-Q3_K_S.gguf` | Q3_K_S | 558 MB | Very Low | Minimal RAM |
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| `PlayerAI-1.2B-v1.5-Q3_K_M.gguf` | Q3_K_M | 600 MB | Low | Low RAM |
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| `PlayerAI-1.2B-v1.5-Q3_K_L.gguf` | Q3_K_L | 635 MB | Low-Med | Low RAM |
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| `PlayerAI-1.2B-v1.5-iQ4_XS.gguf` | IQ4_XS | 669 MB | Medium | Better than Q4 at same size |
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| `PlayerAI-1.2B-v1.5-iQ4_NL.gguf` | IQ4_NL | 700 MB | Medium | Better than Q4 at same size |
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| `PlayerAI-1.2B-v1.5-Q4_K_S.gguf` | Q4_K_S | 700 MB | Medium | Balanced |
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| `PlayerAI-1.2B-v1.5-Q4_K_M.gguf` | Q4_K_M | 731 MB | Medium | ⭐ Recommended |
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| `PlayerAI-1.2B-v1.5-Q5_K_S.gguf` | Q5_K_S | 825 MB | Good | High quality |
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| `PlayerAI-1.2B-v1.5-Q5_K_M.gguf` | Q5_K_M | 843 MB | Good | High quality |
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| `PlayerAI-1.2B-v1.5-Q6_K.gguf` | Q6_K | 963 MB | High | Near lossless |
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| `PlayerAI-1.2B-v1.5-Q8_0.gguf` | Q8_0 | 1.25 GB | Very High | Best quality |
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| `PlayerAI-1.2B-v1.5-BF16.gguf` | BF16 | 2.34 GB | Native precision | Reference |
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| `PlayerAI-1.2B-v1.5-F16.gguf` | F16 | 2.34 GB | Full | Reference / conversion |
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---
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## Which One Should I Pick?
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Since this is a **1.2B model**, all quantizations are lightweight enough for local use.
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```
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Any device with 1GB+ RAM → Q4_K_M ⭐ (recommended)
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Best quality → Q8_0
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Lowest size → Q2_K
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Balanced performance → Q3_K_M / Q4_K_S
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No limits → F16 / BF16
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````
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---
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## How to Use
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### With llama.cpp CLI
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```bash
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hf download YoussefElsafi/PlayerAI-1.2B-v1.5-GGUF \
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PlayerAI-1.2B-v1.5-Q4_K_M.gguf \
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--local-dir ./PlayerAI-GGUF
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./llama.cpp/build/bin/llama-cli \
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-m ./PlayerAI-GGUF/PlayerAI-1.2B-v1.5-Q4_K_M.gguf \
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-p "User: hi\nAI:" \
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-n 100 \
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--temp 0.8 \
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--top-p 0.9
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````
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---
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### With llama-cpp-python
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```python
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from llama_cpp import Llama
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llm = Llama.from_pretrained(
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repo_id="YoussefElsafi/PlayerAI-1.2B-v1.5-GGUF",
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filename="PlayerAI-1.2B-v1.5-Q4_K_M.gguf",
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n_ctx=512,
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verbose=False,
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)
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SYSTEM_PROMPT = (
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"You are a human-like player in a multiplayer chat environment. "
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"Respond casually, with short informal messages and natural tone."
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)
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response = llm.create_chat_completion(
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messages=[
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{"role": "system", "content": SYSTEM_PROMPT},
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{"role": "user", "content": "hi wsp"},
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],
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max_tokens=80,
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temperature=0.8,
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top_p=0.9,
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)
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print(response["choices"][0]["message"]["content"])
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```
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---
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## Model Overview
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* **Base Model:** LiquidAI/LFM2.5-1.2B-Instruct
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* **Parent Model:** PlayerAI-1.2B-v1.5
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* **Parameters:** ~1.2B
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* **Architecture:** Decoder-only Transformer
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* **Training Type:** Supervised fine-tuning (full model)
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* **Context Style:** Multi-turn conversational sequences
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* **Primary Objective:** Social realism in dialogue generation
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---
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## Intended Use
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This model is intended for research and experimental use cases involving:
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* Multiplayer conversational agents
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* Social simulation environments
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* NPC dialogue systems
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* Human-like chat behavior modeling
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* Interactive roleplay systems
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It is not intended for:
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* factual question answering
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* structured instruction following
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* safety-critical systems
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* deterministic reasoning tasks
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---
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## Example Interactions
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**Note:** All assistant messages are generated by PlayerAI-1.2B-v1.5.
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### Example 1 — Single Turn
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### Example 2 — Short Conversation
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### Example 3 — Extended Context Chain
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### Example 4 — Nonsense Interaction
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### Example 5 — Reverse psychology
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---
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## Behavior Characteristics
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The model exhibits:
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* informal conversational tone
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* short and adaptive responses
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* occasional ambiguity or inconsistency
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* strong dependence on recent dialogue context
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* variability in emotional and linguistic style
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These properties are intentional and aligned with the social simulation objective.
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---
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## Limitations
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* Not suitable for factual reasoning tasks
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* May produce inconsistent outputs in long contexts
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* Limited stability in structured instruction formats
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* Not optimized for deterministic responses
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* Can exhibit conversational drift
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---
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## Ethical Considerations
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This model is intended for research and simulation purposes.
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* Outputs may appear human-like in social contexts
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* Behavior is optimized for realism, not correctness
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* Conversational ambiguity is an intentional feature
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Appropriate safeguards should be applied depending on deployment context.
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---
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## Attribution (Optional)
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If you use PlayerAI in a project, attribution is appreciated but not required:
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"**Powered by PlayerAI**"
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---
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## License
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Apache 2.0
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