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

Libraries

How to use Toflamus/Pretrained_evaluated with Transformers:

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

pipe = pipeline("text-generation", model="Toflamus/Pretrained_evaluated")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Toflamus/Pretrained_evaluated")
model = AutoModelForCausalLM.from_pretrained("Toflamus/Pretrained_evaluated", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Toflamus/Pretrained_evaluated with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/Toflamus/Pretrained_evaluated

SGLang

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

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

Pretrained_evaluated

Commit History

Sep 2, 2023

03:21
Adding `safetensors` variant of this model⁠

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initial commit

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Commit History

Sep 2, 2023

Adding `safetensors` variant of this model⁠

Sep 1, 2023

Training in progress step 56000

Training in progress step 48000

Training in progress step 40000

Training in progress step 32000

Training in progress step 24000

Training in progress step 16000

Training in progress step 8000

initial commit