Instructions to use togethercomputer/evo-1-131k-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use togethercomputer/evo-1-131k-base with Transformers:

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

pipe = pipeline("text-generation", model="togethercomputer/evo-1-131k-base", trust_remote_code=True)

# Load model directly
from transformers import AutoModelForCausalLM
model = AutoModelForCausalLM.from_pretrained("togethercomputer/evo-1-131k-base", trust_remote_code=True, dtype="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use togethercomputer/evo-1-131k-base with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "togethercomputer/evo-1-131k-base"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "togethercomputer/evo-1-131k-base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/togethercomputer/evo-1-131k-base

SGLang

How to use togethercomputer/evo-1-131k-base 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 "togethercomputer/evo-1-131k-base" \
    --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": "togethercomputer/evo-1-131k-base",
		"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 "togethercomputer/evo-1-131k-base" \
        --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": "togethercomputer/evo-1-131k-base",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use togethercomputer/evo-1-131k-base with Docker Model Runner:
```
docker model run hf.co/togethercomputer/evo-1-131k-base
```

evo-1-131k-base

Commit History

Update README.md

78c715a
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Zymrael commited on Nov 18, 2024

Update README.md

567369e
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Zymrael commited on Apr 28, 2024

Update README.md

1ec26ca
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Zymrael commited on Apr 28, 2024

fix: fa key in config update

9562f3f
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Zymrael commited on Mar 27, 2024

Update README.md

8eb9480
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Zymrael commited on Feb 27, 2024

Update README.md

36216cf
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Zymrael commited on Feb 27, 2024

Update batch encode plus first argument to match HF convention.

28fe393
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pragaash commited on Feb 27, 2024

Update model.py

60eb4c7
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Zymrael commited on Feb 27, 2024

Update README.md

4a59285
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Zymrael commited on Feb 27, 2024

add pt ckpt

c9e2eda

Zymrael commited on Feb 27, 2024

Update README.md

3fa0ba0
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Zymrael commited on Feb 26, 2024

Fix auto tokenizer import reference format in auto map as list for slow and fast.

a9a132f

Pragaash commited on Feb 26, 2024

Replace tokenizer class with auto map for relative import of byte tokenizer.

72e0b3e
verified

pragaash commited on Feb 26, 2024

Add tokenizer import reference to auto_map in config.json.

29194e9
verified

pragaash commited on Feb 26, 2024

Remove tokenizer.json and replace tokenizer.py with correct version.

ebac1e8
verified

pragaash commited on Feb 26, 2024

Update byte tokenizer to be compatible with auto tokenizer and clean-up.

158e9d1
verified

pragaash commited on Feb 26, 2024