Instructions to use Hplm/dora_llama_model_1850_1880 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Hplm/dora_llama_model_1850_1880 with Transformers:

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

pipe = pipeline("text-generation", model="Hplm/dora_llama_model_1850_1880")

# Load model directly
from transformers import AutoTokenizer, AutoModelForMultimodalLM

tokenizer = AutoTokenizer.from_pretrained("Hplm/dora_llama_model_1850_1880")
model = AutoModelForMultimodalLM.from_pretrained("Hplm/dora_llama_model_1850_1880")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Hplm/dora_llama_model_1850_1880 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_1850_1880"
# 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_1850_1880",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Hplm/dora_llama_model_1850_1880

SGLang

How to use Hplm/dora_llama_model_1850_1880 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_1850_1880" \
    --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_1850_1880",
		"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_1850_1880" \
        --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_1850_1880",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Hplm/dora_llama_model_1850_1880 with Docker Model Runner:
```
docker model run hf.co/Hplm/dora_llama_model_1850_1880
```

dora_llama_model_1850_1880

Commit History

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efittschen commited on Apr 17, 2025

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Elisabeth Fittschen commited on Apr 14, 2025

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Efi commited on Mar 11, 2025

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Commit History

Update README.md 4514ecd verified

Update README.md 472e362 verified

Upload tokenizer a847f2d verified

Upload LlamaForCausalLM 24f26c8 verified

initial commit 685c7d4 verified

Update README.md

4514ecd
verified

Update README.md

472e362
verified

Upload tokenizer

a847f2d
verified

Upload LlamaForCausalLM

24f26c8
verified

initial commit

685c7d4
verified