PlayerAI-1.2B-GGUF/README.md at a2995e84f3a5003446a392941771300402e67a06

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ModelHub XC a2995e84f3 初始化项目，由ModelHub XC社区提供模型

Model: YoussefElsafi/PlayerAI-1.2B-GGUF
Source: Original Platform

2026-05-06 06:22:47 +08:00

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language

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Available Quantizations

File	Quant	Size	Quality	Recommended For
`PlayerAI-1.2B-Q2_K.gguf`	Q2_K	483 MB	Lowest	Very limited RAM
`PlayerAI-1.2B-Q3_K_S.gguf`	Q3_K_S	558 MB	Very Low	Minimal RAM
`PlayerAI-1.2B-Q3_K_M.gguf`	Q3_K_M	600 MB	Low	Low RAM
`PlayerAI-1.2B-Q3_K_L.gguf`	Q3_K_L	635 MB	Low-Med	Low RAM
`PlayerAI-1.2B-IQ4_XS.gguf`	IQ4_XS	669 MB	Medium	Better than Q4 at same size
`PlayerAI-1.2B-IQ4_NL.gguf`	IQ4_NL	700 MB	Medium	Better than Q4 at same size
`PlayerAI-1.2B-Q4_K_S.gguf`	Q4_K_S	700 MB	Medium	Balanced
`PlayerAI-1.2B-Q4_K_M.gguf`	Q4_K_M	731 MB	Medium	⭐ Recommended
`PlayerAI-1.2B-Q5_K_S.gguf`	Q5_K_S	825 MB	Good	High quality
`PlayerAI-1.2B-Q5_K_M.gguf`	Q5_K_M	843 MB	Good	High quality
`PlayerAI-1.2B-Q6_K.gguf`	Q6_K	963 MB	High	Near lossless
`PlayerAI-1.2B-Q8_0.gguf`	Q8_0	1.25 GB	Very High	Best quality
`PlayerAI-1.2B-BF16.gguf`	BF16	2.34 GB	Native precision	Reference
`PlayerAI-1.2B-F16.gguf`	F16	2.34 GB	Full	Reference / conversion

Which One Should I Pick?

Since this is only a 1.2B model, every quantization is very lightweight. Even the highest quality Q8_0 is only 1.25 GB.

Any device with 1GB+ RAM  →  Q4_K_M  ⭐ (only 731 MB)
Want best quality?         →  Q8_0    (only 1.25 GB)
Absolute minimum size?     →  Q2_K    (only 483 MB)
Running on anything?       →  Q3_K_M  (only 600 MB)
No limits at all?          →  BF16 or F16

Bottom line: For a 1.2B model, even a basic laptop or phone can run Q4_K_M or higher with no issues.

How to Use

With llama.cpp CLI

# Download (example: Q4_K_M)
hf download YoussefElsafi/PlayerAI-1.2B-GGUF \
    PlayerAI-1.2B-Q4_K_M.gguf \
    --local-dir ./PlayerAI-GGUF

# Run
./llama.cpp/build/bin/llama-cli \
    -m ./PlayerAI-GGUF/PlayerAI-1.2B-Q4_K_M.gguf \
    -p "User: hi\nAI:" \
    -n 100 \
    --temp 0.8 \
    --top-p 0.9

With llama-cpp-python

from llama_cpp import Llama

llm = Llama.from_pretrained(
    repo_id="YoussefElsafi/PlayerAI-1.2B-GGUF",
    filename="PlayerAI-1.2B-Q4_K_M.gguf",
    n_ctx=512,
    verbose=False,
)

SYSTEM_PROMPT = (
    "You are a human player in a game called Player or AI. "
    "Act like a real human teenager chatting casually. "
    "Use slang, typos, short responses. Never admit you are an AI."
)

response = llm.create_chat_completion(
    messages=[
        {"role": "system", "content": SYSTEM_PROMPT},
        {"role": "user",   "content": "hi wsp"},
    ],
    max_tokens=80,
    temperature=0.8,
    top_p=0.9,
)

print(response["choices"][0]["message"]["content"])

Model Overview

Base Model: LiquidAI/LFM2.5-1.2B-Instruct
Full Precision Model: YoussefElsafi/PlayerAI-1.2B
Parameters: ~1.2B
Architecture: Decoder-only Transformer
Training Type: Supervised fine-tuning (full model)
Context Style: Multi-turn conversational sequences
Primary Objective: Social realism in dialogue generation

Intended Use

This model is intended for research and experimental use cases involving:

Multiplayer conversational agents
Social simulation environments
NPC dialogue systems
Human-like chat behavior modeling
Interactive roleplay systems

It is not intended for:

Factual question answering
Structured instruction following
Safety-critical systems
Deterministic reasoning tasks

Example Interactions

Note: All the white-colored messages are fully generated by PlayerAI-1.2B.

Example 1 — Single Turn

Example 2 — Short Conversation

Example 3 — Extended Context Chain

Example 4 — Nonsense Interaction

Example 5 — Accusation and Denial

Behavior Characteristics

The model exhibits:

Informal conversational tone
Short and adaptive responses
Occasional ambiguity or inconsistency
Strong dependence on recent dialogue context
Variability in emotional and linguistic style

These properties are intentional and aligned with the social simulation objective.

Limitations

Not suitable for factual reasoning tasks
May produce inconsistent outputs in long contexts
Limited stability in structured instruction formats
Not optimized for deterministic responses
Can exhibit unpredictable conversational drift

Ethical Considerations

This model is intended for research and simulation purposes. Developers should be aware that:

Outputs may appear human-like in social contexts
Behavior is optimized for realism, not correctness
Conversational ambiguity is an intentional feature

Appropriate safeguards should be applied depending on deployment context.

Attribution

If you use PlayerAI in a project, attribution is appreciated but not required:

"Powered by PlayerAI"

License

This project is licensed under the Apache 2.0 License.

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