pygmalion-6b
"Pymalion 6B is a proof-of-concept dialogue model based on EleutherAI's GPT-J-6B. **Warning:** This model is **NOT** suitable for use by minors. It **will** output X-rated content under certain circumstances. The fine-tuning dataset consisted of 56MB of dialogue data gathered from multiple sources, w..."
⥠Quick Commands
ollama run pygmalion-6b huggingface-cli download pygmalionai/pygmalion-6b pip install -U transformers Engineering Specs
⥠Hardware
đ§ Lifecycle
đ Identity
Est. VRAM Benchmark
~5.8GB
* Technical estimation for FP16/Q4 weights. Does not include OS overhead or long-context batching. For Technical Reference Only.
đ Interest Trend
Real-time Trend Indexing In-Progress
* Real-time activity index across HuggingFace, GitHub and Research citations.
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Social Proof
đŦTechnical Deep Dive
Full Specifications [+]âž
đ What's Next?
⥠Quick Commands
ollama run pygmalion-6b huggingface-cli download pygmalionai/pygmalion-6b pip install -U transformers Hardware Compatibility
Multi-Tier Validation Matrix
RTX 3060 / 4060 Ti
RTX 4070 Super
RTX 4080 / Mac M3
RTX 3090 / 4090
RTX 6000 Ada
A100 / H100
Pro Tip: Compatibility is estimated for 4-bit quantization (Q4). High-precision (FP16) or ultra-long context windows will significantly increase VRAM requirements.
README
Pygmalion 6B
Model description
Pymalion 6B is a proof-of-concept dialogue model based on EleutherAI's GPT-J-6B.
Warning: This model is NOT suitable for use by minors. It will output X-rated content under certain circumstances.
Training data
The fine-tuning dataset consisted of 56MB of dialogue data gathered from multiple sources, which includes both real and partially machine-generated conversations.
Training procedure
Model weights were initialized from the uft-6b ConvoGPT model made available in this commit.
The model was then further fine-tuned on ~48.5 million tokens for ~5k steps on 4 NVIDIA A40s using DeepSpeed.
Intended use
The easy way
We provide a notebook with a Gradio UI for playing around with the model without having to manually format inputs. This notebook can be found here.
The manual way
The model can be used as a regular text generation model, but it'll perform best if the input prompt adheres to the following format:
[CHARACTER]'s Persona: [A few sentences about the character you want the model to play]
[DIALOGUE HISTORY]
You: [Your input message here]
[CHARACTER]: Where [CHARACTER] is, as you can probably guess, the name of the character you want the model to portray, <START> should be used verbatim as a delimiter token to separate persona and scenario data from the dialogue, and [DIALOGUE HISTORY] is chat history so the model can have some conversational context to draw from. Ideally it'll be pairs of messages like:
[CHARACTER]: [some dialogue here]
You: [your response to the dialogue above]Apart from chat history, you can also just add example conversations in [DIALOGUE HISTORY] to show how the character should speak - ideally at the beginning, so it doesn't get confused as to what's conversation history vs. character definition.
Known issues
We haven't played around with the model enough to enumerate them. Feel free to give us some feedback!
Pygmalion 6B
Model description
Pymalion 6B is a proof-of-concept dialogue model based on EleutherAI's GPT-J-6B.
Warning: This model is NOT suitable for use by minors. It will output X-rated content under certain circumstances.
Training data
The fine-tuning dataset consisted of 56MB of dialogue data gathered from multiple sources, which includes both real and partially machine-generated conversations.
Training procedure
Model weights were initialized from the uft-6b ConvoGPT model made available in this commit.
The model was then further fine-tuned on ~48.5 million tokens for ~5k steps on 4 NVIDIA A40s using DeepSpeed.
Intended use
The easy way
We provide a notebook with a Gradio UI for playing around with the model without having to manually format inputs. This notebook can be found here.
The manual way
The model can be used as a regular text generation model, but it'll perform best if the input prompt adheres to the following format:
[CHARACTER]'s Persona: [A few sentences about the character you want the model to play]
[DIALOGUE HISTORY]
You: [Your input message here]
[CHARACTER]: Where [CHARACTER] is, as you can probably guess, the name of the character you want the model to portray, <START> should be used verbatim as a delimiter token to separate persona and scenario data from the dialogue, and [DIALOGUE HISTORY] is chat history so the model can have some conversational context to draw from. Ideally it'll be pairs of messages like:
[CHARACTER]: [some dialogue here]
You: [your response to the dialogue above]Apart from chat history, you can also just add example conversations in [DIALOGUE HISTORY] to show how the character should speak - ideally at the beginning, so it doesn't get confused as to what's conversation history vs. character definition.
Known issues
We haven't played around with the model enough to enumerate them. Feel free to give us some feedback!
đ Limitations & Considerations
- âĸ Benchmark scores may vary based on evaluation methodology and hardware configuration.
- âĸ VRAM requirements are estimates; actual usage depends on quantization and batch size.
- âĸ FNI scores are relative rankings and may change as new models are added.
- â License Unknown: Verify licensing terms before commercial use.
- âĸ Source: Unknown
Cite this model
Academic & Research Attribution
@misc{hf_model__pygmalionai__pygmalion_6b,
author = {pygmalionai},
title = {undefined Model},
year = {2026},
howpublished = {\url{https://huggingface.co/pygmalionai/pygmalion-6b}},
note = {Accessed via Free2AITools Knowledge Fortress}
}AI Summary: Based on Hugging Face metadata. Not a recommendation.
đĄī¸ Model Transparency Report
Verified data manifest for traceability and transparency.
đ Identity & Source
- id
- hf-model--pygmalionai--pygmalion-6b
- author
- pygmalionai
- tags
- transformerspytorchtensorboardgptjtext-generationtext generationconversationalenlicense:creativeml-openrail-mregion:us
âī¸ Technical Specs
- architecture
- GPTJForCausalLM
- params billions
- 6
- context length
- 4,096
- vram gb
- 5.8
- vram is estimated
- true
- vram formula
- VRAM â (params * 0.75) + 0.8GB (KV) + 0.5GB (OS)
đ Engagement & Metrics
- likes
- 752
- downloads
- 1,504
Free2AITools Constitutional Data Pipeline: Curated disclosure mode active. (V15.x Standard)