Instructions to use ferrazzipietro/meshTask-Llama-3.2-1B-Instruct-ood with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ferrazzipietro/meshTask-Llama-3.2-1B-Instruct-ood with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-3.2-1B-Instruct")
model = PeftModel.from_pretrained(base_model, "ferrazzipietro/meshTask-Llama-3.2-1B-Instruct-ood")

Transformers

How to use ferrazzipietro/meshTask-Llama-3.2-1B-Instruct-ood with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="ferrazzipietro/meshTask-Llama-3.2-1B-Instruct-ood")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("ferrazzipietro/meshTask-Llama-3.2-1B-Instruct-ood", dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ferrazzipietro/meshTask-Llama-3.2-1B-Instruct-ood with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ferrazzipietro/meshTask-Llama-3.2-1B-Instruct-ood"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ferrazzipietro/meshTask-Llama-3.2-1B-Instruct-ood",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/ferrazzipietro/meshTask-Llama-3.2-1B-Instruct-ood

SGLang

How to use ferrazzipietro/meshTask-Llama-3.2-1B-Instruct-ood with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "ferrazzipietro/meshTask-Llama-3.2-1B-Instruct-ood" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ferrazzipietro/meshTask-Llama-3.2-1B-Instruct-ood",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "ferrazzipietro/meshTask-Llama-3.2-1B-Instruct-ood" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ferrazzipietro/meshTask-Llama-3.2-1B-Instruct-ood",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use ferrazzipietro/meshTask-Llama-3.2-1B-Instruct-ood with Docker Model Runner:
```
docker model run hf.co/ferrazzipietro/meshTask-Llama-3.2-1B-Instruct-ood
```

meshTask-Llama-3.2-1B-Instruct-ood

This model is a fine-tuned version of meta-llama/Llama-3.2-1B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.7719
F1 Micro: 0.8692
F1 Macro: 0.8659
F1 Weighted: 0.8697
Class/f1 Results Per Class: {}
Items/f1 Scores Per Item: {'Middle Aged': 0.6260013351134847, 'Rats': 0.8325229605618585, 'Infant': 0.7779635712152881, 'Child, Preschool': 0.8205654079704026, 'Female': 0.5911266307430516, 'Aged, 80 and over': 0.7094054054054054, 'Follow-Up Studies': 0.6711945888534854, 'Child': 0.8401679325482545, 'Retrospective Studies': 0.8577581641659311, 'Reproducibility of Results': 0.6868651488616462, 'Prospective Studies': 0.8444769131149447, 'Cell Proliferation': 0.9267983789260386, 'Cross-Sectional Studies': 0.9179256626065138, 'Young Adult': 0.6342123467721852, 'Adult': 0.7162909836065574}

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0003
train_batch_size: 128
eval_batch_size: 32
seed: 42
distributed_type: multi-GPU
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-07 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	F1 Micro	F1 Macro	F1 Weighted	Class/f1 Results Per Class	Items/f1 Scores Per Item
2.2812	0.0517	20	2.3126	0.5468	0.0090	0.4670	{}	{'Middle Aged': 0.025385597958404654, 'Rats': 0.19322033898305085, 'Infant': 0.2307900432900433, 'Child, Preschool': 0.1258162127727345, 'Female': 0.008606302036301734, 'Aged, 80 and over': 0.1582191780821918, 'Retrospective Studies': 0.15358361774744028, 'Follow-Up Studies': 0.14183222958057395, 'Prospective Studies': 0.14755555555555555, 'Reproducibility of Results': 0.3232678668848882, 'Child': 0.08992293737304823, 'Cell Proliferation': 0.16280566280566283, 'Cross-Sectional Studies': 0.14767255216693417, 'Young Adult': 0.08743288373231226, 'Adult': 0.020321016529547334}
1.8703	0.1034	40	1.9186	0.6565	0.6528	0.6580	{}	{'Middle Aged': 0.5849146110056926, 'Rats': 0.5034399453810199, 'Infant': 0.4675245098039216, 'Child, Preschool': 0.40434647671962876, 'Female': 0.5701056618819776, 'Aged, 80 and over': 0.49995712203070064, 'Retrospective Studies': 0.47506870828425596, 'Follow-Up Studies': 0.5228698096885813, 'Prospective Studies': 0.4850991979738286, 'Reproducibility of Results': 0.4697452229299363, 'Child': 0.39984302097414204, 'Cell Proliferation': 0.46113074204946997, 'Cross-Sectional Studies': 0.5141984425349088, 'Young Adult': 0.43239163524515095, 'Adult': 0.5074738338729294}
1.8016	0.1550	60	1.8633	0.7733	0.7732	0.7740	{}	{'Middle Aged': 0.512987012987013, 'Rats': 0.4966996699669967, 'Infant': 0.608766939936423, 'Child, Preschool': 0.4953854035605849, 'Female': 0.521974306964165, 'Aged, 80 and over': 0.4734980053995246, 'Retrospective Studies': 0.7481872116018458, 'Follow-Up Studies': 0.5964396537644945, 'Prospective Studies': 0.7377746478873239, 'Reproducibility of Results': 0.4714285714285714, 'Child': 0.6344671484712655, 'Cell Proliferation': 0.4899665551839465, 'Cross-Sectional Studies': 0.6886659011864943, 'Young Adult': 0.4867082251738447, 'Adult': 0.4717349783758864}
1.7531	0.2067	80	1.8256	0.8253	0.8243	0.8262	{}	{'Middle Aged': 0.49811876759544294, 'Rats': 0.49586776859504134, 'Infant': 0.7627741306882617, 'Child, Preschool': 0.7854720535901193, 'Female': 0.5048171955983751, 'Aged, 80 and over': 0.5910075329566855, 'Retrospective Studies': 0.8276221902586232, 'Follow-Up Studies': 0.6624316939890711, 'Prospective Studies': 0.724541158087529, 'Reproducibility of Results': 0.47058823529411764, 'Child': 0.8166252690842855, 'Cell Proliferation': 0.6463084654039428, 'Cross-Sectional Studies': 0.7229466437177281, 'Young Adult': 0.4952027978045348, 'Adult': 0.4906238943271612}
1.7297	0.2584	100	1.8041	0.8504	0.8448	0.8491	{}	{'Middle Aged': 0.5780961074830887, 'Rats': 0.783226723525231, 'Infant': 0.7708125061256493, 'Child, Preschool': 0.726111758572042, 'Female': 0.5454735740450026, 'Aged, 80 and over': 0.5811371841155235, 'Retrospective Studies': 0.8211651662714219, 'Follow-Up Studies': 0.5824132492113565, 'Prospective Studies': 0.8664169787765293, 'Reproducibility of Results': 0.47058823529411764, 'Child': 0.8384231757361574, 'Cell Proliferation': 0.7075743048897412, 'Cross-Sectional Studies': 0.690931832395247, 'Young Adult': 0.5815810665712241, 'Adult': 0.5920607214640854}
1.7156	0.3101	120	1.7973	0.8462	0.8374	0.8429	{}	{'Middle Aged': 0.6543482799042935, 'Rats': 0.6633554083885209, 'Infant': 0.7319096985122189, 'Child, Preschool': 0.7442220336444866, 'Female': 0.642816021054363, 'Aged, 80 and over': 0.6075811660717321, 'Retrospective Studies': 0.827579766536965, 'Follow-Up Studies': 0.5225906631937487, 'Prospective Studies': 0.8223247232472324, 'Reproducibility of Results': 0.47058823529411764, 'Child': 0.8233540553313702, 'Cell Proliferation': 0.5749721293199554, 'Cross-Sectional Studies': 0.7511748120300752, 'Young Adult': 0.5314276289825707, 'Adult': 0.7112988932282618}
1.7094	0.3618	140	1.7929	0.8669	0.8641	0.8669	{}	{'Middle Aged': 0.5386918726166814, 'Rats': 0.783226723525231, 'Infant': 0.8101498445009896, 'Child, Preschool': 0.8303125707570056, 'Female': 0.5646041055718475, 'Aged, 80 and over': 0.7163398692810458, 'Retrospective Studies': 0.8673170010715737, 'Follow-Up Studies': 0.6475638977635783, 'Prospective Studies': 0.8775488972118186, 'Reproducibility of Results': 0.4976533690915186, 'Child': 0.8509083527859536, 'Cell Proliferation': 0.692436974789916, 'Cross-Sectional Studies': 0.7857462305136724, 'Young Adult': 0.653471504832577, 'Adult': 0.6339317959036268}
1.7172	0.4134	160	1.7887	0.8441	0.8436	0.8449	{}	{'Middle Aged': 0.46697555932954293, 'Rats': 0.7466777408637874, 'Infant': 0.8251302083333334, 'Child, Preschool': 0.7757352941176471, 'Female': 0.5048171955983751, 'Aged, 80 and over': 0.6242931641115859, 'Retrospective Studies': 0.8374161858180473, 'Follow-Up Studies': 0.7175497866287339, 'Prospective Studies': 0.858901098901099, 'Reproducibility of Results': 0.6146552689536751, 'Child': 0.8535637149028078, 'Cell Proliferation': 0.8641909341882625, 'Cross-Sectional Studies': 0.792301498823238, 'Young Adult': 0.4790233484608908, 'Adult': 0.49398578458173864}
1.7141	0.4651	180	1.7850	0.8687	0.8655	0.8685	{}	{'Middle Aged': 0.5707346690953248, 'Rats': 0.783226723525231, 'Infant': 0.814365821094793, 'Child, Preschool': 0.840034965034965, 'Female': 0.5646041055718475, 'Aged, 80 and over': 0.7171552407139861, 'Retrospective Studies': 0.8419891534148358, 'Follow-Up Studies': 0.5904033854344414, 'Prospective Studies': 0.8576749135408352, 'Reproducibility of Results': 0.47058823529411764, 'Child': 0.848669375608081, 'Cell Proliferation': 0.692436974789916, 'Cross-Sectional Studies': 0.7857462305136724, 'Young Adult': 0.6674364392932616, 'Adult': 0.6623577196225313}
1.7109	0.5168	200	1.7822	0.8735	0.8689	0.8725	{}	{'Middle Aged': 0.6538360098464424, 'Rats': 0.783226723525231, 'Infant': 0.7903993025944246, 'Child, Preschool': 0.8044570030987688, 'Female': 0.7081618612796298, 'Aged, 80 and over': 0.622690929142542, 'Retrospective Studies': 0.8682561103613735, 'Follow-Up Studies': 0.6104005713172758, 'Prospective Studies': 0.8644043931286962, 'Reproducibility of Results': 0.4976533690915186, 'Child': 0.8609630054958576, 'Cell Proliferation': 0.692436974789916, 'Cross-Sectional Studies': 0.7857462305136724, 'Young Adult': 0.656353465007421, 'Adult': 0.7528357579590976}
1.6938	0.5685	220	1.7804	0.8642	0.8572	0.8618	{}	{'Middle Aged': 0.707550514002127, 'Rats': 0.783226723525231, 'Infant': 0.7667524487800985, 'Child, Preschool': 0.7629142269245913, 'Female': 0.7701488154541546, 'Aged, 80 and over': 0.5845301083396321, 'Retrospective Studies': 0.8342013888888888, 'Follow-Up Studies': 0.5509660386415456, 'Prospective Studies': 0.8438856566457121, 'Reproducibility of Results': 0.47058823529411764, 'Child': 0.8397862362307776, 'Cell Proliferation': 0.7075743048897412, 'Cross-Sectional Studies': 0.778341303192774, 'Young Adult': 0.5982878399266217, 'Adult': 0.7588436265651368}
1.7016	0.6202	240	1.7782	0.8714	0.8696	0.8718	{}	{'Middle Aged': 0.5310245310245311, 'Rats': 0.783226723525231, 'Infant': 0.823894113549286, 'Child, Preschool': 0.8609422492401215, 'Female': 0.5646041055718475, 'Aged, 80 and over': 0.7076925571327815, 'Retrospective Studies': 0.8777244289247781, 'Follow-Up Studies': 0.7089757757547054, 'Prospective Studies': 0.8793233082706767, 'Reproducibility of Results': 0.6680644828652941, 'Child': 0.8541968489677653, 'Cell Proliferation': 0.8282657657657657, 'Cross-Sectional Studies': 0.7930274938594406, 'Young Adult': 0.6462431418828829, 'Adult': 0.6640632333890317}
1.7031	0.6718	260	1.7770	0.8780	0.8742	0.8774	{}	{'Middle Aged': 0.6712682966357026, 'Rats': 0.783226723525231, 'Infant': 0.8012578616352202, 'Child, Preschool': 0.8513615858276532, 'Female': 0.7344456156931167, 'Aged, 80 and over': 0.7252547543324463, 'Retrospective Studies': 0.8735556090515166, 'Follow-Up Studies': 0.6075094081423196, 'Prospective Studies': 0.8644043931286962, 'Reproducibility of Results': 0.5233713654766287, 'Child': 0.8505807373875751, 'Cell Proliferation': 0.692436974789916, 'Cross-Sectional Studies': 0.7857462305136724, 'Young Adult': 0.652116782772532, 'Adult': 0.7721004678650578}
1.7047	0.7235	280	1.7752	0.8823	0.8792	0.8820	{}	{'Middle Aged': 0.6617876191046923, 'Rats': 0.783226723525231, 'Infant': 0.808614898966726, 'Child, Preschool': 0.8493827160493828, 'Female': 0.7344456156931167, 'Aged, 80 and over': 0.7345676773538372, 'Retrospective Studies': 0.8796762260557448, 'Follow-Up Studies': 0.6943722943722943, 'Prospective Studies': 0.8775488972118186, 'Reproducibility of Results': 0.610640163694826, 'Child': 0.8505807373875751, 'Cell Proliferation': 0.7882154548159905, 'Cross-Sectional Studies': 0.7930274938594406, 'Young Adult': 0.6834744203165255, 'Adult': 0.7700621118012423}
1.7016	0.7752	300	1.7740	0.8810	0.8786	0.8811	{}	{'Middle Aged': 0.6354422676310184, 'Rats': 0.783226723525231, 'Infant': 0.8213175007068136, 'Child, Preschool': 0.8675550257567373, 'Female': 0.617747771477687, 'Aged, 80 and over': 0.7341677895184738, 'Retrospective Studies': 0.8894195976262845, 'Follow-Up Studies': 0.6822205551387848, 'Prospective Studies': 0.8793233082706767, 'Reproducibility of Results': 0.610640163694826, 'Child': 0.8586845761926818, 'Cell Proliferation': 0.7882154548159905, 'Cross-Sectional Studies': 0.7930274938594406, 'Young Adult': 0.6703104120572192, 'Adult': 0.7519431787724471}
1.7109	0.8269	320	1.7728	0.8810	0.8781	0.8808	{}	{'Middle Aged': 0.6696530233115598, 'Rats': 0.783226723525231, 'Infant': 0.82296918767507, 'Child, Preschool': 0.861882325034772, 'Female': 0.6341775599128541, 'Aged, 80 and over': 0.704803427798241, 'Retrospective Studies': 0.8849422948362877, 'Follow-Up Studies': 0.675456016475434, 'Prospective Studies': 0.8710280373831776, 'Reproducibility of Results': 0.610640163694826, 'Child': 0.8654761904761905, 'Cell Proliferation': 0.7882154548159905, 'Cross-Sectional Studies': 0.7930274938594406, 'Young Adult': 0.6759713540678416, 'Adult': 0.7497513681695698}
1.6875	0.8786	340	1.7725	0.8815	0.8792	0.8816	{}	{'Middle Aged': 0.6354422676310184, 'Rats': 0.783226723525231, 'Infant': 0.823894113549286, 'Child, Preschool': 0.8675550257567373, 'Female': 0.6341775599128541, 'Aged, 80 and over': 0.7344249952945605, 'Retrospective Studies': 0.8815708837122114, 'Follow-Up Studies': 0.7089757757547054, 'Prospective Studies': 0.8793233082706767, 'Reproducibility of Results': 0.6305958132045089, 'Child': 0.8709643932315997, 'Cell Proliferation': 0.7882154548159905, 'Cross-Sectional Studies': 0.7930274938594406, 'Young Adult': 0.6772037107052642, 'Adult': 0.7327786642352405}
1.6875	0.9302	360	1.7723	0.8808	0.8781	0.8808	{}	{'Middle Aged': 0.6539275202354673, 'Rats': 0.783226723525231, 'Infant': 0.8213175007068136, 'Child, Preschool': 0.8675550257567373, 'Female': 0.6341775599128541, 'Aged, 80 and over': 0.7134910751349107, 'Retrospective Studies': 0.8888403899316164, 'Follow-Up Studies': 0.6943722943722943, 'Prospective Studies': 0.8664169787765293, 'Reproducibility of Results': 0.5897943185635895, 'Child': 0.8665354330708661, 'Cell Proliferation': 0.7882154548159905, 'Cross-Sectional Studies': 0.7930274938594406, 'Young Adult': 0.6730322188185709, 'Adult': 0.7472290657672471}
1.6797	0.9819	380	1.7721	0.8818	0.8790	0.8817	{}	{'Middle Aged': 0.6638190159784845, 'Rats': 0.783226723525231, 'Infant': 0.807303249874453, 'Child, Preschool': 0.858553761593954, 'Female': 0.6341775599128541, 'Aged, 80 and over': 0.7192571888767825, 'Retrospective Studies': 0.8879107981220657, 'Follow-Up Studies': 0.6657010751490168, 'Prospective Studies': 0.883969912387903, 'Reproducibility of Results': 0.5934065934065934, 'Child': 0.8665354330708661, 'Cell Proliferation': 0.7882154548159905, 'Cross-Sectional Studies': 0.7930274938594406, 'Young Adult': 0.6804812036600116, 'Adult': 0.7544007076514816}

Framework versions

PEFT 0.18.1
Transformers 4.51.0
Pytorch 2.8.0+cu128
Datasets 3.6.0
Tokenizers 0.21.0

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