Question Answering
Safetensors
Italian
llama
llama-3
meta
medical-qa
italian
biomedical
fine-tuning
unsloth
bnb
4bit
imb
Neurologia
Instructions to use praiselab-picuslab/Llama-3.2-1B-Instruct-Neurologia with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Local Apps
- Unsloth Studio new
How to use praiselab-picuslab/Llama-3.2-1B-Instruct-Neurologia 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 praiselab-picuslab/Llama-3.2-1B-Instruct-Neurologia 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 praiselab-picuslab/Llama-3.2-1B-Instruct-Neurologia to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for praiselab-picuslab/Llama-3.2-1B-Instruct-Neurologia to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="praiselab-picuslab/Llama-3.2-1B-Instruct-Neurologia", max_seq_length=2048, )
File size: 234 Bytes
14617d4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | {
"bos_token_id": 128000,
"do_sample": true,
"eos_token_id": [
128001,
128008,
128009
],
"max_length": 131072,
"pad_token_id": 128004,
"temperature": 0.6,
"top_p": 0.9,
"transformers_version": "4.57.1"
}
|