Instructions to use gkMSDA/Llama-2-7b-FinChatGTP298_Model_1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use gkMSDA/Llama-2-7b-FinChatGTP298_Model_1 with Transformers:

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

pipe = pipeline("text-generation", model="gkMSDA/Llama-2-7b-FinChatGTP298_Model_1")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("gkMSDA/Llama-2-7b-FinChatGTP298_Model_1")
model = AutoModelForCausalLM.from_pretrained("gkMSDA/Llama-2-7b-FinChatGTP298_Model_1", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use gkMSDA/Llama-2-7b-FinChatGTP298_Model_1 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "gkMSDA/Llama-2-7b-FinChatGTP298_Model_1"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "gkMSDA/Llama-2-7b-FinChatGTP298_Model_1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/gkMSDA/Llama-2-7b-FinChatGTP298_Model_1

SGLang

How to use gkMSDA/Llama-2-7b-FinChatGTP298_Model_1 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 "gkMSDA/Llama-2-7b-FinChatGTP298_Model_1" \
    --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": "gkMSDA/Llama-2-7b-FinChatGTP298_Model_1",
		"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 "gkMSDA/Llama-2-7b-FinChatGTP298_Model_1" \
        --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": "gkMSDA/Llama-2-7b-FinChatGTP298_Model_1",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use gkMSDA/Llama-2-7b-FinChatGTP298_Model_1 with Docker Model Runner:
```
docker model run hf.co/gkMSDA/Llama-2-7b-FinChatGTP298_Model_1
```

Llama-2-7b-FinChatGTP298_Model_1

Commit History

Upload tokenizer

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gkMSDA commited on Mar 12, 2024

Upload LlamaForCausalLM

0221b13
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gkMSDA commited on Mar 12, 2024

Upload tokenizer

1d1e46c
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GY commited on Mar 12, 2024

Upload LlamaForCausalLM

7e5be5a
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GY commited on Mar 12, 2024

initial commit

7fa99e5
verified

GY commited on Mar 12, 2024

Commit History

Upload tokenizer bf8e99f verified

Upload LlamaForCausalLM 0221b13 verified

Upload tokenizer 1d1e46c verified

Upload LlamaForCausalLM 7e5be5a verified

initial commit 7fa99e5 verified

Upload tokenizer

bf8e99f
verified

Upload LlamaForCausalLM

0221b13
verified

Upload tokenizer

1d1e46c
verified

Upload LlamaForCausalLM

7e5be5a
verified

initial commit

7fa99e5
verified