README.md

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license: apache-2.0 tags:

• LoRA

• 4-bit

• BF16

• FlashAttn2

• Pokémon

• EMA

• fast-training

• text-generation

• chat

• transformers language: en datasets:

• ogmatrixllm/pokemon-lore-instructions finetuned_from: Qwen/Qwen2.5-7B-Instruct tasks:

• text-generation

  Qwen2.5-Coder-7B LoRA 4-bit BF16 w/ FlashAttn2, short seq=512 for faster iteration

  This is a LoRA-fused model based on Qwen/Qwen2.5-7B-Instruct.

  Model Description

  • Model Name: Qwen2.5-Coder-7B LoRA 4-bit BF16 w/ FlashAttn2, short seq=512 for faster iteration
  • Language: en
  • License: apache-2.0
  • Dataset: ogmatrixllm/pokemon-lore-instructions
  • Tags: LoRA, 4-bit, BF16, FlashAttn2, Pokémon, EMA, fast-training, text-generation, chat, transformers

  Usage

  from transformers import AutoTokenizer, AutoModelForCausalLM
  
  tokenizer = AutoTokenizer.from_pretrained("ogmatrixllm/arcadex-llm")
  model = AutoModelForCausalLM.from_pretrained("ogmatrixllm/arcadex-llm")
  
  prompt = "Hello, world!"
  inputs = tokenizer(prompt, return_tensors="pt")
  outputs = model.generate(**inputs)
  print(tokenizer.decode(outputs[0], skip_special_tokens=True))