First model version

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README.md

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+---
+license: agpl-3.0
+language:
+- en
+thumbnail:
+tags:
+- text generation
+- conversational
+inference: false
+
+---
+
+# Pygmalion 1.3B
+
+## Model description
+
+Pymalion 1.3B is a proof-of-concept dialogue model based on EleutherAI's [pythia-1.3b-deduped](https://huggingface.co/EleutherAI/pythia-1.3b-deduped).
+
+**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
+
+Fine-tuning was done using [ColossalAI](https://github.com/hpcaitech/ColossalAI) (specifically, with a slightly modified version of their [OPT fine-tune example](https://github.com/hpcaitech/ColossalAI/blob/78509124d32b63b7fc36f6508e0576a326d51422/examples/language/opt/run_clm.py)) for around 11.4 million tokens over 5440 steps on a single 24GB GPU. The run took just under 21 hours.
+
+## 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](https://github.com/PygmalionAI/gradio-ui/blob/master/notebooks/GPU.ipynb).
+
+### 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, 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
+
+- The model can get stuck repeating certain phrases, or sometimes even entire sentences.
+  - We believe this is due to that behavior being present in the training data itself, and plan to investigate and adjust accordingly for future versions.

config.json

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+  "hidden_act": "gelu",
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+  "initializer_range": 0.02,
+  "intermediate_size": 8192,
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 2048,
+  "model_type": "gpt_neox",
+  "num_attention_heads": 16,
+  "num_hidden_layers": 24,
+  "rotary_emb_base": 10000,
+  "rotary_pct": 0.25,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.25.1",
+  "use_cache": true,
+  "use_parallel_residual": true,
+  "vocab_size": 50304
+}

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special_tokens_map.json

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tokenizer_config.json

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+  "tokenizer_class": "GPTNeoXTokenizer",
+  "unk_token": "<|endoftext|>"
+}