Instructions to use oddadmix/Emhotob-25M-English-MSA-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use oddadmix/Emhotob-25M-English-MSA-v1 with Transformers:

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

pipe = pipeline("text-generation", model="oddadmix/Emhotob-25M-English-MSA-v1")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("oddadmix/Emhotob-25M-English-MSA-v1")
model = AutoModelForCausalLM.from_pretrained("oddadmix/Emhotob-25M-English-MSA-v1", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use oddadmix/Emhotob-25M-English-MSA-v1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "oddadmix/Emhotob-25M-English-MSA-v1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "oddadmix/Emhotob-25M-English-MSA-v1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/oddadmix/Emhotob-25M-English-MSA-v1

SGLang

How to use oddadmix/Emhotob-25M-English-MSA-v1 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 "oddadmix/Emhotob-25M-English-MSA-v1" \
    --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": "oddadmix/Emhotob-25M-English-MSA-v1",
		"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 "oddadmix/Emhotob-25M-English-MSA-v1" \
        --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": "oddadmix/Emhotob-25M-English-MSA-v1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use oddadmix/Emhotob-25M-English-MSA-v1 with Docker Model Runner:
```
docker model run hf.co/oddadmix/Emhotob-25M-English-MSA-v1
```

Emhotob-25M-English-MSA-v1 / tokenizer_config.json

oddadmix

English-MSA 25M SFT + card + eval

f11e07f verified 3 months ago

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346 Bytes

	{
	"backend": "tokenizers",
	"bos_token": "<s>",
	"eos_token": "<\|im_end\|>",
	"extra_special_tokens": [
	"<\|im_start\|>",
	"<\|im_end\|>"
	],
	"is_local": false,
	"local_files_only": false,
	"model_max_length": 1000000000000000019884624838656,
	"pad_token": "<pad>",
	"tokenizer_class": "TokenizersBackend",
	"unk_token": "<unk>"
	}