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Meta-Llama-3.1-8B-Instruct-reuploaded – AI Model by rombodawg | AlphaNeural AI
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Meta-Llama-3.1-8B-Instruct-reuploaded
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transformers
safetensors
llama
text-generation
llama-3
meta
facebook
unsloth
conversational
en
rombodawg/Meta-Llama-3.1-8B-reuploaded
finetune
llama3.1
autotrain_compatible
text-generation-inference
endpoints_compatible
us
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Finetune Llama 3.1, Gemma 2, Mistral 2-5x faster with 70% less memory via Unsloth!
We have a free Google Colab Tesla T4 notebook for Llama 3.1 (8B) here:
https://colab.research.google.com/drive/1Ys44kVvmeZtnICzWz0xgpRnrIOjZAuxp?usp=sharing
✨ Finetune for Free
All notebooks are
beginner friendly
! Add your dataset, click "Run All", and you'll get a 2x faster finetuned model which can be exported to GGUF, vLLM or uploaded to Hugging Face.
Unsloth supports
Free Notebooks
Performance
Memory use
Llama-3 8b
▶️ Start on Colab
2.4x faster
58% less
Gemma 7b
▶️ Start on Colab
2.4x faster
58% less
Mistral 7b
▶️ Start on Colab
2.2x faster
62% less
|
Llama-2 7b
|
▶️ Start on Colab
| 2.2x faster | 43% less | |
TinyLlama
|
▶️ Start on Colab
| 3.9x faster | 74% less | |
CodeLlama 34b
A100 |
▶️ Start on Colab
| 1.9x faster | 27% less | |
Mistral 7b
1xT4 |
▶️ Start on Kaggle
| 5x faster* | 62% less | |
DPO - Zephyr
|
▶️ Start on Colab
| 1.9x faster | 19% less |
This
conversational notebook
is useful for ShareGPT ChatML / Vicuna templates.
This
text completion notebook
is for raw text. This
DPO notebook
replicates Zephyr.
* Kaggle has 2x T4s, but we use 1. Due to overhead, 1x T4 is 5x faster.