Text Generation
Transformers
Safetensors
mistral
Not-For-All-Audiences
nsfw
text-generation-inference
Inference Endpoints
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README.md ADDED
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+ ---
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+ datasets:
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+ - Squish42/bluemoon-fandom-1-1-rp-cleaned
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+ - OpenLeecher/Teatime
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+ - PygmalionAI/PIPPA
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+ tags:
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+ - not-for-all-audiences
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+ - nsfw
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+ license: cc-by-nc-4.0
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+ ---
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+ ## What is PetrolLM-Claude-Chat?
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+ PetrolLM-Claude-Chat is the [CollectiveCognition-v1.1-Mistral-7B](https://huggingface.co/teknium/CollectiveCognition-v1.1-Mistral-7B) model with the [PetrolLoRA](https://huggingface.co/Norquinal/PetrolLoRA) applied.
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+
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+ The dataset (for the LoRA) consists of 2800 samples, with the composition as follows:
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+ * AICG Logs (~34%)
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+ * PygmalionAI/PIPPA (~33%)
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+ * Squish42/bluemoon-fandom-1-1-rp-cleaned (~29%)
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+ * OpenLeecher/Teatime (~4%)
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+
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+ These samples were then back-filled using gpt-4/gpt-3.5-turbo-16k or otherwise converted to fit the prompt format.
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+
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+ ## Prompt Format
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+ The model uses the following prompt format:
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+ ```
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+ ---
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+ style: roleplay
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+ characters:
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+ [char]: [description]
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+ summary: [scenario]
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+ ---
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+ <chat_history>
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+ Format:
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+ [char]: [message]
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+ Human: [message]
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+ ```
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+
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+ ## Use in Text Generation Web UI
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+ Install the bleeding-edge version of `transformers` from source:
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+ ```
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+ pip install git+https://github.com/huggingface/transformers
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+ ```
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+ Or, alternatively, change `model_type` in `config.json` from `mistral` to `llama`.
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+
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+ ## Use in SillyTavern UI
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+ ![](https://files.catbox.moe/2dkr28.png)
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+ As an addendum, you can include one of the following as the `Last Output Sequence`:
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+ ```
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+ Human: In your next reply, write at least two paragraphs. Be descriptive and immersive, providing vivid details about {{char}}'s actions, emotions, and the environment.
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+ {{char}}:
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+ ```
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+ ```
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+ {{char}} (2 paragraphs, engaging, natural, authentic, descriptive, creative):
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+ ```
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+ ```
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+ [System note: Write at least two paragraphs. Be descriptive and immersive, providing vivid details about {{char}}'s actions, emotions, and the environment.]
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+ {{char}}:
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+ ```
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+ The third one seems to work the best. I would recommend experimenting with creating your own to best suit your needs.
config.json ADDED
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+ {
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+ "_name_or_path": "teknium/CollectiveCognition-v1.1-Mistral-7B",
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+ "architectures": [
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+ "MistralForCausalLM"
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+ ],
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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "hidden_act": "silu",
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+ "hidden_size": 4096,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 14336,
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+ "max_position_embeddings": 32768,
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+ "model_type": "mistral",
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+ "num_attention_heads": 32,
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+ "num_hidden_layers": 32,
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+ "num_key_value_heads": 8,
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+ "rms_norm_eps": 1e-05,
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+ "rope_theta": 10000.0,
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+ "sliding_window": 4096,
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+ "tie_word_embeddings": false,
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+ "torch_dtype": "float16",
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+ "transformers_version": "4.35.0.dev0",
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+ "use_cache": false,
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+ "vocab_size": 32000
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+ }
generation_config.json ADDED
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+ {
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+ "_from_model_config": true,
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+ "bos_token_id": 1,
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+ "eos_token_id": 2,
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+ "transformers_version": "4.35.0.dev0"
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+ }
huggingface-metadata.txt ADDED
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+ url: https://huggingface.co/Norquinal/PetrolLM-CollectiveCognition
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+ branch: main
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+ download date: 2023-10-13 12:09:09
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+ sha256sum:
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+ 86d82ef4705d55edcd80925088dc9d814c30cf47859894b862f9321940ba13b6 pytorch_model-00001-of-00002.bin
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+ aadf970b5b3269d507c1d452e87f62fde74b7a5177fb28a82520b9b18ae47d16 pytorch_model-00002-of-00002.bin
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