Instructions to use nazdef/1gpu-llm-medium-en-it-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use nazdef/1gpu-llm-medium-en-it-base with Transformers:

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

pipe = pipeline("text-generation", model="nazdef/1gpu-llm-medium-en-it-base")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("nazdef/1gpu-llm-medium-en-it-base")
model = AutoModelForCausalLM.from_pretrained("nazdef/1gpu-llm-medium-en-it-base")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use nazdef/1gpu-llm-medium-en-it-base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "nazdef/1gpu-llm-medium-en-it-base"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "nazdef/1gpu-llm-medium-en-it-base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/nazdef/1gpu-llm-medium-en-it-base

SGLang

How to use nazdef/1gpu-llm-medium-en-it-base 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 "nazdef/1gpu-llm-medium-en-it-base" \
    --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": "nazdef/1gpu-llm-medium-en-it-base",
		"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 "nazdef/1gpu-llm-medium-en-it-base" \
        --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": "nazdef/1gpu-llm-medium-en-it-base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use nazdef/1gpu-llm-medium-en-it-base with Docker Model Runner:
```
docker model run hf.co/nazdef/1gpu-llm-medium-en-it-base
```

1gpu-llm-medium-en-it-base / metrics.json

nazdef

release: publish official 1gpu-llm medium base from step14700

52ee5b8 verified 7 days ago

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2.47 kB

	{
	"checkpoints": {
	"manual-manual-step_14700-14700": {
	"aggregate_validation_loss_mean": null,
	"aggregate_validation_perplexity_mean": null,
	"checkpoint_name": "step_14700",
	"checkpoint_selector": "manual",
	"checkpoint_step": 14700,
	"cloze_en_contains": 0.16,
	"cloze_en_exact": 0.0,
	"cloze_it_contains": 0.24,
	"cloze_it_exact": 0.0,
	"distinct_1": 0.27804410354745923,
	"distinct_2": 0.5643070787637089,
	"language_consistency_en": 1.0,
	"language_consistency_it": 0.85,
	"language_switch_rate_en": 0.0,
	"language_switch_rate_it": 0.0,
	"loop_rate": 0.375,
	"ppl_en": 80.87098332928396,
	"ppl_it": 35.982162207895115,
	"ppl_mixed": 85.07813449956652,
	"repeated_4gram_rate": 0.75,
	"source_loss_books_en": 4.411039806547619,
	"source_loss_books_it": 4.39037105015346,
	"source_loss_code": 7.720833333333333,
	"source_loss_web_en": 5.489309210526316,
	"source_loss_web_it": 5.4087171052631575,
	"source_loss_wiki_en": 2.9984019886363638,
	"source_loss_wiki_it": 2.92021484375,
	"val_loss_en": 4.392855086416568,
	"val_loss_it": 3.5830233214331453,
	"val_loss_mixed": 4.443570063664363
	}
	},
	"cloze_en_contains": 0.16,
	"cloze_en_exact": 0.0,
	"cloze_it_contains": 0.24,
	"cloze_it_exact": 0.0,
	"distinct_1": 0.27804410354745923,
	"distinct_2": 0.5643070787637089,
	"language_consistency_en": 1.0,
	"language_consistency_it": 0.85,
	"language_switch_rate_en": 0.0,
	"language_switch_rate_it": 0.0,
	"loop_rate": 0.375,
	"ppl_en": 80.87098332928396,
	"ppl_it": 35.982162207895115,
	"ppl_mixed": 85.07813449956652,
	"recommended_checkpoint": {
	"checkpoint_name": "step_14700",
	"checkpoint_path": "/mnt/apps/llm-nanochat/checkpoints/20260629_resume-gpt2medium-gpt2preln-k20-wsddecayonly-rerunmissing-lr3p5294e5-anchor20k-final2e5-webwiki-step14200-to14850/step_14700.pt",
	"direction": "min",
	"value": 4.443570063664363
	},
	"recommended_metric": "val_loss_mixed",
	"repeated_4gram_rate": 0.75,
	"source_losses": {
	"books_en": 4.411039806547619,
	"books_it": 4.39037105015346,
	"code": 7.720833333333333,
	"web_en": 5.489309210526316,
	"web_it": 5.4087171052631575,
	"wiki_en": 2.9984019886363638,
	"wiki_it": 2.92021484375
	},
	"val_loss_en": 4.392855086416568,
	"val_loss_it": 3.5830233214331453,
	"val_loss_mixed": 4.443570063664363
	}