Instructions to use Achyuth4/FlawlessAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Achyuth4/FlawlessAI with Transformers:

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

pipe = pipeline("text-generation", model="Achyuth4/FlawlessAI")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, OpenGPT

tokenizer = AutoTokenizer.from_pretrained("Achyuth4/FlawlessAI")
model = OpenGPT.from_pretrained("Achyuth4/FlawlessAI")
messages = [
    {"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
	messages,
	add_generation_prompt=True,
	tokenize=True,
	return_dict=True,
	return_tensors="pt",
).to(model.device)

outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Achyuth4/FlawlessAI with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Achyuth4/FlawlessAI"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Achyuth4/FlawlessAI",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Achyuth4/FlawlessAI

SGLang

How to use Achyuth4/FlawlessAI 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 "Achyuth4/FlawlessAI" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Achyuth4/FlawlessAI",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

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 "Achyuth4/FlawlessAI" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Achyuth4/FlawlessAI",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Achyuth4/FlawlessAI with Docker Model Runner:
```
docker model run hf.co/Achyuth4/FlawlessAI
```

N.Achyuth Reddy commited on Oct 1, 2023

Commit

ffefe87

1 Parent(s): 4309cc1

Update README.md

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@@ -3,13 +3,26 @@ license: apache-2.0
 pipeline_tag: text-generation
 tags:
 - finetuned
 ---
-# Model Card for Mistral-7B-Instruct-v0.1
-The Mistral-7B-Instruct-v0.1 Large Language Model (LLM) is a instruct fine-tuned version of the [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) generative text model using a variety of publicly available conversation datasets.
-For full details of this model please read our [release blog post](https://mistral.ai/news/announcing-mistral-7b/)
 ## Instruction format
@@ -29,8 +42,8 @@ from transformers import AutoModelForCausalLM, AutoTokenizer
 device = "cuda" # the device to load the model onto
-model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1")
-tokenizer = AutoTokenizer.from_pretrained("mistralai/Mistral-7B-Instruct-v0.1")
 messages = [
     {"role": "user", "content": "What is your favourite condiment?"},

 pipeline_tag: text-generation
 tags:
 - finetuned
+- chatgpt
+- LLM
+- openGPT
+- free LLM
+- no api key
+- LLAMA
+- llama chat
+- opengpt model
+- opengpt llm
+- text-to-text
+- Text-to-Text
+- Chatbot
+- Chat UI
 ---
+# Model Card for OpenGPT-1.0
+The OpenGPT-1.0 Large Language Model (LLM) is a instruct fine-tuned version of the [OpenGPT-1.0](https://huggingface.co/AchyuthGamer/OpenGPT) generative text model using a variety of publicly available conversation datasets.
+For full details of this model please read our [release blog post](https://huggingface.co/AchyuthGamer/OpenGPT)
 ## Instruction format
 device = "cuda" # the device to load the model onto
+model = AutoModelForCausalLM.from_pretrained("AchyuthGamer/OpenGPT")
+tokenizer = AutoTokenizer.from_pretrained("AchyuthGamer/OpenGPT")
 messages = [
     {"role": "user", "content": "What is your favourite condiment?"},