Instructions to use Braywayc/ingredients_to_recipe_llama-3.2-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Braywayc/ingredients_to_recipe_llama-3.2-model with Transformers:

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

pipe = pipeline("text-generation", model="Braywayc/ingredients_to_recipe_llama-3.2-model")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Braywayc/ingredients_to_recipe_llama-3.2-model")
model = AutoModelForCausalLM.from_pretrained("Braywayc/ingredients_to_recipe_llama-3.2-model")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Braywayc/ingredients_to_recipe_llama-3.2-model with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Braywayc/ingredients_to_recipe_llama-3.2-model"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Braywayc/ingredients_to_recipe_llama-3.2-model",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Braywayc/ingredients_to_recipe_llama-3.2-model

SGLang

How to use Braywayc/ingredients_to_recipe_llama-3.2-model 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 "Braywayc/ingredients_to_recipe_llama-3.2-model" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Braywayc/ingredients_to_recipe_llama-3.2-model",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

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 "Braywayc/ingredients_to_recipe_llama-3.2-model" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Braywayc/ingredients_to_recipe_llama-3.2-model",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Braywayc/ingredients_to_recipe_llama-3.2-model with Docker Model Runner:
```
docker model run hf.co/Braywayc/ingredients_to_recipe_llama-3.2-model
```

ingredients_to_recipe_llama-3.2-model

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

Loss: 0.6841

Model description

This is llama 3.2 1B fine-tuned on an ingredients_to_recipe dataset.

Intended uses & limitations

For best performance, prompt should follow this format: [INST] Generate a cooking recipe using the following ingredients:1 c. firmly packed brown sugar, 1/2 c. evaporated milk, 1/2 tsp. vanilla, 1/2 c. broken nuts (pecans), 2 Tbsp. butter or margarine, 3 1/2 c. bite size shredded rice biscuits [/INST]

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 24
eval_batch_size: 24
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
0.7335	1.0	2500	0.6922
0.6345	2.0	5000	0.6790
0.6034	3.0	7500	0.6841

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.19.1

Downloads last month: 33

Safetensors

Model size

1B params

Tensor type

BF16

Model tree for Braywayc/ingredients_to_recipe_llama-3.2-model

Base model

meta-llama/Llama-3.2-1B

Finetuned

(936)

this model