Instructions to use Hplm/dora_llama_model_1910_1940 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Hplm/dora_llama_model_1910_1940 with Transformers:

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

pipe = pipeline("text-generation", model="Hplm/dora_llama_model_1910_1940")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Hplm/dora_llama_model_1910_1940")
model = AutoModelForCausalLM.from_pretrained("Hplm/dora_llama_model_1910_1940", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Hplm/dora_llama_model_1910_1940 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_1910_1940"
# 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_1910_1940",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Hplm/dora_llama_model_1910_1940

SGLang

How to use Hplm/dora_llama_model_1910_1940 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_1910_1940" \
    --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_1910_1940",
		"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_1910_1940" \
        --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_1910_1940",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Hplm/dora_llama_model_1910_1940 with Docker Model Runner:
```
docker model run hf.co/Hplm/dora_llama_model_1910_1940
```

dora_llama_model_1910_1940

Commit History

Improve model card: Add metadata, link to paper and code, and basic description

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nielsr HF Staff commited on Apr 11, 2025

Upload tokenizer

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Efi commited on Mar 5, 2025

Upload LlamaForCausalLM

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Efi commited on Mar 5, 2025

initial commit

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Efi commited on Mar 5, 2025

Commit History

Improve model card: Add metadata, link to paper and code, and basic description a3f52b1 verified

Upload tokenizer f7b0f47 verified

Upload LlamaForCausalLM d0ec7aa verified

initial commit 1af2abb verified

Improve model card: Add metadata, link to paper and code, and basic description

a3f52b1
verified

Upload tokenizer

f7b0f47
verified

Upload LlamaForCausalLM

d0ec7aa
verified

initial commit

1af2abb
verified