Instructions to use Hplm/dora_llama_model_1750_1820 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Hplm/dora_llama_model_1750_1820 with Transformers:

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

pipe = pipeline("text-generation", model="Hplm/dora_llama_model_1750_1820")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Hplm/dora_llama_model_1750_1820")
model = AutoModelForCausalLM.from_pretrained("Hplm/dora_llama_model_1750_1820")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Hplm/dora_llama_model_1750_1820 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Hplm/dora_llama_model_1750_1820"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Hplm/dora_llama_model_1750_1820",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Hplm/dora_llama_model_1750_1820

SGLang

How to use Hplm/dora_llama_model_1750_1820 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 "Hplm/dora_llama_model_1750_1820" \
    --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": "Hplm/dora_llama_model_1750_1820",
		"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 "Hplm/dora_llama_model_1750_1820" \
        --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": "Hplm/dora_llama_model_1750_1820",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Hplm/dora_llama_model_1750_1820 with Docker Model Runner:
```
docker model run hf.co/Hplm/dora_llama_model_1750_1820
```

dora_llama_model_1750_1820

Commit History

Update README.md

cc10fc4
verified

efittschen commited on Apr 17, 2025

Update README.md

e5966f8
verified

Elisabeth Fittschen commited on Apr 14, 2025

Upload tokenizer

5f2671d
verified

Efi commited on Feb 28, 2025

Upload LlamaForCausalLM

e654579
verified

Efi commited on Feb 28, 2025

initial commit

d522e1f
verified

Efi commited on Feb 28, 2025

Commit History

Update README.md cc10fc4 verified

Update README.md e5966f8 verified

Upload tokenizer 5f2671d verified

Upload LlamaForCausalLM e654579 verified

initial commit d522e1f verified

Update README.md

cc10fc4
verified

Update README.md

e5966f8
verified

Upload tokenizer

5f2671d
verified

Upload LlamaForCausalLM

e654579
verified

initial commit

d522e1f
verified