| --- | |
| 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 | |
| ```python | |
| 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)) | |