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README.md
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---
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license: apache-2.0
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datasets:
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-
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- IlyaGusev/gpt_roleplay_realm
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- tamohannes/llm-roleplay
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- radce/communication_dataset
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("
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model = AutoModelForCausalLM.from_pretrained("
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def chat(messages, temp=0.5):
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inputs = tokenizer.apply_chat_template(messages, return_tensors="pt")
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Sources:
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-
- `
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- `IlyaGusev/gpt_roleplay_realm`
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- `tamohannes/llm-roleplay`
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- `radce/communication_dataset`
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("
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model = AutoModelForCausalLM.from_pretrained("
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def chat(messages, temp=0.5):
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inputs = tokenizer.apply_chat_template(messages, return_tensors="pt")
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Источники:
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-
- `
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- `IlyaGusev/gpt_roleplay_realm`
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- `tamohannes/llm-roleplay`
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- `radce/communication_dataset`
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---
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license: apache-2.0
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datasets:
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- limloop/characters_dialogs
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- IlyaGusev/gpt_roleplay_realm
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- tamohannes/llm-roleplay
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- radce/communication_dataset
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("limloop/whiff-mamba2-20M")
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model = AutoModelForCausalLM.from_pretrained("limloop/whiff-mamba2-20M")
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def chat(messages, temp=0.5):
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inputs = tokenizer.apply_chat_template(messages, return_tensors="pt")
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Sources:
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+
- `limloop/characters_dialogs`
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- `IlyaGusev/gpt_roleplay_realm`
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- `tamohannes/llm-roleplay`
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- `radce/communication_dataset`
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```python
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained("limloop/whiff-mamba2-20M")
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model = AutoModelForCausalLM.from_pretrained("limloop/whiff-mamba2-20M")
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def chat(messages, temp=0.5):
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inputs = tokenizer.apply_chat_template(messages, return_tensors="pt")
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Источники:
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+
- `limloop/characters_dialogs`
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- `IlyaGusev/gpt_roleplay_realm`
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- `tamohannes/llm-roleplay`
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- `radce/communication_dataset`
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