Instructions to use Devam42/adapter_model.safetensors with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Devam42/adapter_model.safetensors with Transformers:

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

pipe = pipeline("text-generation", model="Devam42/adapter_model.safetensors")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Devam42/adapter_model.safetensors")
model = AutoModelForCausalLM.from_pretrained("Devam42/adapter_model.safetensors")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Devam42/adapter_model.safetensors with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Devam42/adapter_model.safetensors"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Devam42/adapter_model.safetensors",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/Devam42/adapter_model.safetensors

SGLang

How to use Devam42/adapter_model.safetensors 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 "Devam42/adapter_model.safetensors" \
    --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": "Devam42/adapter_model.safetensors",
		"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 "Devam42/adapter_model.safetensors" \
        --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": "Devam42/adapter_model.safetensors",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use Devam42/adapter_model.safetensors with Docker Model Runner:
```
docker model run hf.co/Devam42/adapter_model.safetensors
```

Devam42 commited on May 9, 2024

Commit

bdf623b

verified ·

1 Parent(s): ad395b0

Delete special_tokens_map.json

Browse files

Files changed (1) hide show

special_tokens_map.json +0 -23

special_tokens_map.json DELETED Viewed

@@ -1,23 +0,0 @@
-{
-  "bos_token": {
-    "content": "<|begin_of_text|>",
-    "lstrip": false,
-    "normalized": false,
-    "rstrip": false,
-    "single_word": false
-  },
-  "eos_token": {
-    "content": "<|end_of_text|>",
-    "lstrip": false,
-    "normalized": false,
-    "rstrip": false,
-    "single_word": false
-  },
-  "pad_token": {
-    "content": "<|end_of_text|>",
-    "lstrip": false,
-    "normalized": false,
-    "rstrip": false,
-    "single_word": false
-  }
-}