Instructions to use fay-ong/new-llamafactory-llama-3-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use fay-ong/new-llamafactory-llama-3-8b with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/llama-3-8b-Instruct-bnb-4bit") model = PeftModel.from_pretrained(base_model, "fay-ong/new-llamafactory-llama-3-8b") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use fay-ong/new-llamafactory-llama-3-8b 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 fay-ong/new-llamafactory-llama-3-8b 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 fay-ong/new-llamafactory-llama-3-8b to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for fay-ong/new-llamafactory-llama-3-8b to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="fay-ong/new-llamafactory-llama-3-8b", max_seq_length=2048, )
End of training
Browse files- README.md +3 -2
- all_results.json +8 -0
- train_results.json +8 -0
- trainer_state.json +84 -0
README.md
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library_name: peft
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license: llama3.1
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tags:
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- unsloth
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- llama-factory
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- generated_from_trainer
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model-index:
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- name: new-llamafactory-llama-3-8b
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# new-llamafactory-llama-3-8b
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This model is a fine-tuned version of [unsloth/llama-3-8b-Instruct-bnb-4bit](https://huggingface.co/unsloth/llama-3-8b-Instruct-bnb-4bit) on
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## Model description
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library_name: peft
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license: llama3.1
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tags:
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- llama-factory
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- lora
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- unsloth
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- generated_from_trainer
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model-index:
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- name: new-llamafactory-llama-3-8b
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# new-llamafactory-llama-3-8b
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This model is a fine-tuned version of [unsloth/llama-3-8b-Instruct-bnb-4bit](https://huggingface.co/unsloth/llama-3-8b-Instruct-bnb-4bit) on the formatted_data dataset.
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## Model description
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all_results.json
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{
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"epoch": 0.992,
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"total_flos": 1.6166347506450432e+16,
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"train_loss": 0.15166758986250048,
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"train_runtime": 892.7422,
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"train_steps_per_second": 0.069
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}
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train_results.json
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{
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"epoch": 0.992,
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"total_flos": 1.6166347506450432e+16,
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"train_loss": 0.15166758986250048,
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"train_runtime": 892.7422,
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"train_samples_per_second": 0.56,
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"train_steps_per_second": 0.069
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}
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trainer_state.json
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