Instructions to use INC4AI/neural-chat-7b-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use INC4AI/neural-chat-7b-v3 with Transformers:

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

pipe = pipeline("text-generation", model="INC4AI/neural-chat-7b-v3")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("INC4AI/neural-chat-7b-v3")
model = AutoModelForCausalLM.from_pretrained("INC4AI/neural-chat-7b-v3", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use INC4AI/neural-chat-7b-v3 with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "INC4AI/neural-chat-7b-v3"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "INC4AI/neural-chat-7b-v3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/INC4AI/neural-chat-7b-v3

SGLang

How to use INC4AI/neural-chat-7b-v3 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 "INC4AI/neural-chat-7b-v3" \
    --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": "INC4AI/neural-chat-7b-v3",
		"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 "INC4AI/neural-chat-7b-v3" \
        --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": "INC4AI/neural-chat-7b-v3",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use INC4AI/neural-chat-7b-v3 with Docker Model Runner:
```
docker model run hf.co/INC4AI/neural-chat-7b-v3
```

lvkaokao commited on Nov 6, 2023

Commit

7a05c8a

1 Parent(s): 972bfe2

update model.

Browse files

Files changed (3) hide show

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@@ -16,7 +16,7 @@ We use the [Eleuther AI Language Model Evaluation Harness](https://github.com/El
 | Model | Average ⬆️| ARC (25-s) ⬆️ | HellaSwag (10-s) ⬆️ | MMLU (5-s) ⬆️| TruthfulQA (MC) (0-s) ⬆️ |
 | --- | --- | --- | --- | --- | --- |
 |[mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) | 62.4 | 59.58  | 83.31  | 64.16  | 42.15 |
-| **Ours** | **67.92** | 66.29 | 83.28 | 62.11  | 60.02 |
 ## Training procedure

 | Model | Average ⬆️| ARC (25-s) ⬆️ | HellaSwag (10-s) ⬆️ | MMLU (5-s) ⬆️| TruthfulQA (MC) (0-s) ⬆️ |
 | --- | --- | --- | --- | --- | --- |
 |[mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) | 62.4 | 59.58  | 83.31  | 64.16  | 42.15 |
+| **Ours** | **67.82** | 67.41 | 82.63 | 61.69  | 59.57 |
 ## Training procedure

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