Instructions to use Jithendra-k/interACT_LLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Jithendra-k/interACT_LLM with Transformers:

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

pipe = pipeline("text-generation", model="Jithendra-k/interACT_LLM")

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

tokenizer = AutoTokenizer.from_pretrained("Jithendra-k/interACT_LLM")
model = AutoModelForCausalLM.from_pretrained("Jithendra-k/interACT_LLM", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Jithendra-k/interACT_LLM with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/Jithendra-k/interACT_LLM

SGLang

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

Docker Model Runner
How to use Jithendra-k/interACT_LLM with Docker Model Runner:
```
docker model run hf.co/Jithendra-k/interACT_LLM
```

interACT_LLM

Commit History

Apr 21

03:41
Adding `safetensors` variant of this model⁠

SFconvertbot

Verified signature
50724c8

Apr 26, 2024

05:34
Update README.md

Jithendra-k

Verified signature
8a9b596
04:44
Update README.md

Jithendra-k

Verified signature
792e1cf

Apr 15, 2024

21:45
Update README.md

Jithendra-k

Verified signature
c1b095d
20:47
Update README.md

Jithendra-k

Verified signature
c5772ab
20:44
Update README.md

Jithendra-k

Verified signature
ab1a7b3
20:27
Upload tokenizer

Jithendra-k

Verified signature
8aea824
20:27
Upload LlamaForCausalLM

Jithendra-k

Verified signature
25aa9ae
20:12
Example Input-Output

Jithendra-k

Verified signature
4ed0ed3
20:10
Update README.md

Jithendra-k

Verified signature
a2eaa61
19:18
Update README.md

Jithendra-k

Verified signature
1a83a32

Apr 14, 2024

08:49
Upload tokenizer

Jithendra-k

Verified signature
550d9be
08:49
Upload LlamaForCausalLM

Jithendra-k

Verified signature
a01dec4
08:41
initial commit

Jithendra-k

Verified signature
c43c94c

Commit History

Apr 21

Adding `safetensors` variant of this model⁠

Apr 26, 2024

Update README.md

Update README.md

Apr 15, 2024

Update README.md

Update README.md

Update README.md

Upload tokenizer

Upload LlamaForCausalLM

Example Input-Output

Update README.md

Update README.md

Apr 14, 2024

Upload tokenizer

Upload LlamaForCausalLM

initial commit