Question Answering
Safetensors
Italian
llama
llama-3
meta
medical-qa
italian
biomedical
fine-tuning
unsloth
bnb
4bit
imb
Oculistica
Instructions to use praiselab-picuslab/Llama-3.2-1B-Instruct-Oculistica 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-Oculistica 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-Oculistica 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-Oculistica 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-Oculistica 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-Oculistica", max_seq_length=2048, )
File size: 915 Bytes
593c682 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 | {
"architectures": [
"LlamaForCausalLM"
],
"attention_bias": false,
"attention_dropout": 0.0,
"bos_token_id": 128000,
"dtype": "float16",
"eos_token_id": 128009,
"head_dim": 64,
"hidden_act": "silu",
"hidden_size": 2048,
"initializer_range": 0.02,
"intermediate_size": 8192,
"max_position_embeddings": 131072,
"mlp_bias": false,
"model_type": "llama",
"num_attention_heads": 32,
"num_hidden_layers": 16,
"num_key_value_heads": 8,
"pad_token_id": 128004,
"pretraining_tp": 1,
"rms_norm_eps": 1e-05,
"rope_scaling": {
"factor": 32.0,
"high_freq_factor": 4.0,
"low_freq_factor": 1.0,
"original_max_position_embeddings": 8192,
"rope_type": "llama3"
},
"rope_theta": 500000.0,
"tie_word_embeddings": true,
"transformers_version": "4.57.1",
"unsloth_fixed": true,
"unsloth_version": "2026.5.2",
"use_cache": true,
"vocab_size": 128256
}
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