Instructions to use wqerrewetw/Qwen-2.5-7B-1M-RRP-v1-lora-F16-GGUF with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use wqerrewetw/Qwen-2.5-7B-1M-RRP-v1-lora-F16-GGUF with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("wqerrewetw/Qwen-2.5-7B-1M-RRP-v1-lora-F16-GGUF", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use wqerrewetw/Qwen-2.5-7B-1M-RRP-v1-lora-F16-GGUF with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for wqerrewetw/Qwen-2.5-7B-1M-RRP-v1-lora-F16-GGUF to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for wqerrewetw/Qwen-2.5-7B-1M-RRP-v1-lora-F16-GGUF to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for wqerrewetw/Qwen-2.5-7B-1M-RRP-v1-lora-F16-GGUF to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="wqerrewetw/Qwen-2.5-7B-1M-RRP-v1-lora-F16-GGUF", max_seq_length=2048, )
Upload README.md with huggingface_hub
Browse files
README.md
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---
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base_model: bunnycore/Qwen-2.5-7B-1M-RRP-v1-lora
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tags:
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- text-generation-inference
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- transformers
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- unsloth
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- qwen2
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- trl
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- llama-cpp
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- gguf-my-lora
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license: apache-2.0
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language:
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- en
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datasets:
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- AMead10/Sky-T1_data_17k_sharegpt
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- Chaser-cz/sonnet35-charcard-roleplay-sharegpt
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---
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# wqerrewetw/Qwen-2.5-7B-1M-RRP-v1-lora-F16-GGUF
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This LoRA adapter was converted to GGUF format from [`bunnycore/Qwen-2.5-7B-1M-RRP-v1-lora`](https://huggingface.co/bunnycore/Qwen-2.5-7B-1M-RRP-v1-lora) via the ggml.ai's [GGUF-my-lora](https://huggingface.co/spaces/ggml-org/gguf-my-lora) space.
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Refer to the [original adapter repository](https://huggingface.co/bunnycore/Qwen-2.5-7B-1M-RRP-v1-lora) for more details.
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## Use with llama.cpp
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```bash
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# with cli
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llama-cli -m base_model.gguf --lora Qwen-2.5-7B-1M-RRP-v1-lora-f16.gguf (...other args)
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# with server
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llama-server -m base_model.gguf --lora Qwen-2.5-7B-1M-RRP-v1-lora-f16.gguf (...other args)
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```
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To know more about LoRA usage with llama.cpp server, refer to the [llama.cpp server documentation](https://github.com/ggerganov/llama.cpp/blob/master/examples/server/README.md).
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