Instructions to use togethercomputer/GPT-NeoXT-Chat-Base-20B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use togethercomputer/GPT-NeoXT-Chat-Base-20B with Transformers:

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

pipe = pipeline("text-generation", model="togethercomputer/GPT-NeoXT-Chat-Base-20B")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("togethercomputer/GPT-NeoXT-Chat-Base-20B")
model = AutoModelForCausalLM.from_pretrained("togethercomputer/GPT-NeoXT-Chat-Base-20B", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use togethercomputer/GPT-NeoXT-Chat-Base-20B with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "togethercomputer/GPT-NeoXT-Chat-Base-20B"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "togethercomputer/GPT-NeoXT-Chat-Base-20B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/togethercomputer/GPT-NeoXT-Chat-Base-20B

SGLang

How to use togethercomputer/GPT-NeoXT-Chat-Base-20B 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 "togethercomputer/GPT-NeoXT-Chat-Base-20B" \
    --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": "togethercomputer/GPT-NeoXT-Chat-Base-20B",
		"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 "togethercomputer/GPT-NeoXT-Chat-Base-20B" \
        --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": "togethercomputer/GPT-NeoXT-Chat-Base-20B",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use togethercomputer/GPT-NeoXT-Chat-Base-20B with Docker Model Runner:
```
docker model run hf.co/togethercomputer/GPT-NeoXT-Chat-Base-20B
```

juewang commited on Mar 7, 2023

Commit

1bff121

1 Parent(s): 9caedd0

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@@ -6,9 +6,14 @@ language:
 # GPT-NeoXT-Chat-Base-20B
-GPT-NeoXT-Chat-Base-20B is a 20B parameter open source chat model, fine-tuned from EleutherAI’s GPT-NeoX with over 40 million instructions on 100% carbon negative compute.
-It is part of OpenChatKit (codebase available [here](https://github.com/togethercomputer/OpenChaT))
-a community project that enables the open source AI contributors to improve the datasets available for training large language models and chatbots.
 ## Model Details
 - **Developed by**: \[TODO\] Together Computer, LAION, Ontocord, ...
@@ -21,6 +26,13 @@ a community project that enables the open source AI contributors to improve the
 ## Examples
 \[TODO\] sync with the blog post
 # Uses
 \[TODO\]
@@ -78,11 +90,9 @@ We therefore welcome contributions from individuals and organizations, and encou
 \[TODO\]
 **Training Procedure**
-\[TODO\]
-\[TODO\]
 - **Hardware:** 2 x 8 x A100 GPUs
-- **Optimizer:** AdamW
 - **Gradient Accumulations**: 2
 - **Batch:** 2 x 2 x 64 x 2048 = 524288 tokens
 - **Learning rate:** warmup to 1e-6 for 100 steps and then kept constant

 # GPT-NeoXT-Chat-Base-20B
+> TLDR: As part of OpenChatKit (codebase available [here](https://github.com/togethercomputer/OpenChaT)),
+> GPT-NeoXT-Chat-Base-20B is a 20B parameter language model, fine-tuned from EleutherAI’s GPT-NeoX with over 40 million instructions on 100% carbon negative compute.
+We base GPT-NeoXT-Chat-Base-20B on ElutherAI’s GPT-NeoX model, and fine-tune it with data focusing on dialog-style interactions.
+We focused the tuning on several tasks such as question answering, classification, extraction, and summarization.
+We’ve fine-tuned the model with a collection of 43 million high-quality instructions.
+Together partnered with LAION and Ontocord, who both helped curate the dataset the model is based on.
+You can read more about this process and the availability of this dataset in LAION’s blog post [here](...).
 ## Model Details
 - **Developed by**: \[TODO\] Together Computer, LAION, Ontocord, ...
 ## Examples
 \[TODO\] sync with the blog post
+## Training Examples
+The training data consists of pairs of human queries and corresponding bot responses, with human queries prefixed with <human>: and bot responses prefixed with <bot>:.
+An example of the data format is as follows:
 # Uses
 \[TODO\]
 \[TODO\]
 **Training Procedure**
 - **Hardware:** 2 x 8 x A100 GPUs
+- **Optimizer:** [8bit-AdamW](https://github.com/TimDettmers/bitsandbytes)
 - **Gradient Accumulations**: 2
 - **Batch:** 2 x 2 x 64 x 2048 = 524288 tokens
 - **Learning rate:** warmup to 1e-6 for 100 steps and then kept constant