Instructions to use ahmed792002/alzheimers_memory_support_ai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ahmed792002/alzheimers_memory_support_ai with Transformers:

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

pipe = pipeline("text-generation", model="ahmed792002/alzheimers_memory_support_ai")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ahmed792002/alzheimers_memory_support_ai")
model = AutoModelForCausalLM.from_pretrained("ahmed792002/alzheimers_memory_support_ai")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use ahmed792002/alzheimers_memory_support_ai with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ahmed792002/alzheimers_memory_support_ai"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ahmed792002/alzheimers_memory_support_ai",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ahmed792002/alzheimers_memory_support_ai

SGLang

How to use ahmed792002/alzheimers_memory_support_ai 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 "ahmed792002/alzheimers_memory_support_ai" \
    --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": "ahmed792002/alzheimers_memory_support_ai",
		"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 "ahmed792002/alzheimers_memory_support_ai" \
        --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": "ahmed792002/alzheimers_memory_support_ai",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ahmed792002/alzheimers_memory_support_ai with Docker Model Runner:
```
docker model run hf.co/ahmed792002/alzheimers_memory_support_ai
```

custom_model

This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.7420

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: 0.0002
train_batch_size: 4
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 50

Training results

Training Loss	Epoch	Step	Validation Loss
1.4865	1.0	369	1.3129
1.2021	2.0	738	1.1809
1.0322	3.0	1107	1.1234
0.9008	4.0	1476	1.0991
0.8134	5.0	1845	1.0827
0.7293	6.0	2214	1.0923
0.6539	7.0	2583	1.0942
0.5962	8.0	2952	1.1175
0.546	9.0	3321	1.1365
0.4915	10.0	3690	1.1490
0.4523	11.0	4059	1.1860
0.4204	12.0	4428	1.1977
0.3831	13.0	4797	1.2311
0.357	14.0	5166	1.2499
0.3378	15.0	5535	1.2674
0.3203	16.0	5904	1.2902
0.2943	17.0	6273	1.3226
0.2796	18.0	6642	1.3355
0.2679	19.0	7011	1.3618
0.2479	20.0	7380	1.3775
0.2361	21.0	7749	1.3995
0.2274	22.0	8118	1.4151
0.2102	23.0	8487	1.4315
0.1994	24.0	8856	1.4490
0.1943	25.0	9225	1.4714
0.1777	26.0	9594	1.4906
0.1697	27.0	9963	1.5078
0.1602	28.0	10332	1.5293
0.1497	29.0	10701	1.5457
0.1403	30.0	11070	1.5652
0.1315	31.0	11439	1.5814
0.124	32.0	11808	1.5987
0.1142	33.0	12177	1.6151
0.1057	34.0	12546	1.6354
0.1002	35.0	12915	1.6508
0.093	36.0	13284	1.6641
0.0867	37.0	13653	1.6808
0.081	38.0	14022	1.6866
0.076	39.0	14391	1.7061
0.0716	40.0	14760	1.7150
0.067	41.0	15129	1.7232
0.0638	42.0	15498	1.7322
0.0598	43.0	15867	1.7388
0.0575	44.0	16236	1.7446
0.0539	45.0	16605	1.7524
0.0525	46.0	16974	1.7580
0.0505	47.0	17343	1.7609
0.0479	48.0	17712	1.7612
0.0473	49.0	18081	1.7642
0.0462	50.0	18450	1.7644

Framework versions

Transformers 4.39.3
Pytorch 2.1.2
Datasets 2.18.0
Tokenizers 0.15.2

Downloads last month: 3

Safetensors

Model size

0.1B params

Tensor type

F32

Model tree for ahmed792002/alzheimers_memory_support_ai

Base model

openai-community/gpt2

Finetuned

(2153)

this model

ahmed792002
/

alzheimers_memory_support_ai

custom_model

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Model tree for ahmed792002/alzheimers_memory_support_ai

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