Instructions to use jphme/em_german_mistral_v01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jphme/em_german_mistral_v01 with Transformers:

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

pipe = pipeline("text-generation", model="jphme/em_german_mistral_v01")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("jphme/em_german_mistral_v01")
model = AutoModelForCausalLM.from_pretrained("jphme/em_german_mistral_v01")

Inference
Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use jphme/em_german_mistral_v01 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "jphme/em_german_mistral_v01"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "jphme/em_german_mistral_v01",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/jphme/em_german_mistral_v01

SGLang

How to use jphme/em_german_mistral_v01 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 "jphme/em_german_mistral_v01" \
    --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": "jphme/em_german_mistral_v01",
		"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 "jphme/em_german_mistral_v01" \
        --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": "jphme/em_german_mistral_v01",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use jphme/em_german_mistral_v01 with Docker Model Runner:
```
docker model run hf.co/jphme/em_german_mistral_v01
```

em_german_mistral_v01

Commit History

update readme

1cd12da

jphme commited on Oct 12, 2023

update readme

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830154e

jphme commited on Oct 4, 2023

update readme

6dd5ab0

jphme commited on Oct 4, 2023

update readme

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jphme commited on Oct 4, 2023

update readme

617dd54

jphme commited on Oct 4, 2023

fix tokenizer

8b01cea

jphme commited on Oct 3, 2023

remove added tokens json

5c43cef

Jan Philipp Harries commited on Oct 3, 2023

fix tokenizer

e6dcdd3

jphme commited on Oct 3, 2023

merged model upload

400ffc6

jphme commited on Oct 2, 2023

Create README.md

0e64a4a

jphme commited on Sep 28, 2023

merged model upload

9bdffb8

jphme commited on Sep 28, 2023

initial commit

e3d87fc

jphme commited on Sep 28, 2023

Commit History

update readme 1cd12da

update readme d8970de

update readme 830154e

update readme 6dd5ab0

update readme 9859a40

update readme 617dd54

fix tokenizer 8b01cea

remove added tokens json 5c43cef

fix tokenizer e6dcdd3

merged model upload 400ffc6

Create README.md 0e64a4a

merged model upload 9bdffb8

initial commit e3d87fc

update readme

1cd12da

update readme

d8970de

update readme

830154e

update readme

6dd5ab0

update readme

9859a40

update readme

617dd54

fix tokenizer

8b01cea

remove added tokens json

5c43cef

fix tokenizer

e6dcdd3

merged model upload

400ffc6

Create README.md

0e64a4a

merged model upload

9bdffb8

initial commit

e3d87fc