Instructions to use jojo-ai-mst/MyanmarGPT-Chat with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use jojo-ai-mst/MyanmarGPT-Chat with Transformers:

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

pipe = pipeline("text-generation", model="jojo-ai-mst/MyanmarGPT-Chat")

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("jojo-ai-mst/MyanmarGPT-Chat")
model = AutoModelForCausalLM.from_pretrained("jojo-ai-mst/MyanmarGPT-Chat", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use jojo-ai-mst/MyanmarGPT-Chat with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/jojo-ai-mst/MyanmarGPT-Chat

SGLang

How to use jojo-ai-mst/MyanmarGPT-Chat 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 "jojo-ai-mst/MyanmarGPT-Chat" \
    --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": "jojo-ai-mst/MyanmarGPT-Chat",
		"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 "jojo-ai-mst/MyanmarGPT-Chat" \
        --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": "jojo-ai-mst/MyanmarGPT-Chat",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use jojo-ai-mst/MyanmarGPT-Chat with Docker Model Runner:
```
docker model run hf.co/jojo-ai-mst/MyanmarGPT-Chat
```

jojo-ai-mst commited on Feb 25, 2024

Commit

19df9ba

verified ·

1 Parent(s): d159916

Update README.md

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README.md +17 -19

README.md CHANGED Viewed

@@ -58,17 +58,14 @@ Thus, MyanmarGPT-Chat is required to build a foundational model for question-ans
 <!-- Provide a longer summary of what this model is. -->
 - **Developed by:** [Min Si Thu](https://huggingface.co/jojo-ai-mst)
-- **Funded by [self]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
 - **Model type:** GPT2
 - **Language(s) (NLP):** Burmese, English
 - **License:** CreativeML OpenRAIL-M
 - **Finetuned from model [MyanmarGPT]:** [MyanmarGPT](https://huggingface.co/jojo-ai-mst/MyanmarGPT)
-### Model Sources [optional]
 <!-- Provide the basic links for the model. -->
@@ -76,13 +73,10 @@ Thus, MyanmarGPT-Chat is required to build a foundational model for question-ans
 - **Paper [optional]:** [More Information Needed]
 - **Demo [optional]:** [More Information Needed]
-## Uses
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
 ### Direct Use
 <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
 Originally crafted for text completion in Burmese, this model functions as a fundamental asset for various Natural Language Processing (NLP) tasks. Although its primary role is presently centered on aiding in text generation and completion, it harbors considerable potential for broader applications. Researchers and developers have the option to refine this model using specialized datasets, thereby expanding its utility to other NLP domains, including summarization and instruction-based tasks. Nevertheless, it is crucial to acknowledge that when dealing with high-stakes decisions or comprehending domain-specific terminology, additional specialized training for the model is advised to ensure optimal accuracy and reliability.
@@ -90,20 +84,15 @@ Originally crafted for text completion in Burmese, this model functions as a fun
 Users need to recognize the inherent limitations and biases present in language models. Responsible usage is crucial, particularly in sensitive contexts, as this model is not designed to generate misleading or harmful content.
-[More Information Needed]
 ## Bias, Risks, and Limitations
-While the MyanmarGPT-Chat excels in handling general Burmese text about history of countires around the world, its effectiveness might be limited when dealing with daily-life spoken burmese words. Users are encouraged to perform comprehensive testing tailored to their specific use cases.
-[More Information Needed]
 ### Recommendations
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
 ## How to Get Started with the Model
 ```shell
@@ -137,10 +126,19 @@ generate_text("User: မြန်မာနိုင်ငံအကြောင
-## Citation [optional]
 - MinSithu, MyanmarGPT, https://huggingface.co/jojo-ai-mst/MyanmarGPT, 1.1-SweptWood
-## Model Card Contact
-[More Information Needed]

 <!-- Provide a longer summary of what this model is. -->
 - **Developed by:** [Min Si Thu](https://huggingface.co/jojo-ai-mst)
+- **Funded by:** Self
 - **Model type:** GPT2
 - **Language(s) (NLP):** Burmese, English
 - **License:** CreativeML OpenRAIL-M
 - **Finetuned from model [MyanmarGPT]:** [MyanmarGPT](https://huggingface.co/jojo-ai-mst/MyanmarGPT)
+### Model Sources
 <!-- Provide the basic links for the model. -->
 - **Paper [optional]:** [More Information Needed]
 - **Demo [optional]:** [More Information Needed]
 ### Direct Use
 <!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+Question Answering GPT for Burmese Language.
 Originally crafted for text completion in Burmese, this model functions as a fundamental asset for various Natural Language Processing (NLP) tasks. Although its primary role is presently centered on aiding in text generation and completion, it harbors considerable potential for broader applications. Researchers and developers have the option to refine this model using specialized datasets, thereby expanding its utility to other NLP domains, including summarization and instruction-based tasks. Nevertheless, it is crucial to acknowledge that when dealing with high-stakes decisions or comprehending domain-specific terminology, additional specialized training for the model is advised to ensure optimal accuracy and reliability.
 Users need to recognize the inherent limitations and biases present in language models. Responsible usage is crucial, particularly in sensitive contexts, as this model is not designed to generate misleading or harmful content.
 ## Bias, Risks, and Limitations
+While the MyanmarGPT-Chat excels in handling general Burmese text about the history of countries around the world, its effectiveness might be limited when dealing with daily-life spoken burmese words. Users are encouraged to perform comprehensive testing tailored to their specific use cases.
 ### Recommendations
+Users (both direct and downstream) should be made aware of the risks, biases, and limitations of the model.
 ## How to Get Started with the Model
 ```shell
+## Citations [optional]
 - MinSithu, MyanmarGPT, https://huggingface.co/jojo-ai-mst/MyanmarGPT, 1.1-SweptWood
+## How to cite this project
+```
+@software{MyanmarGPT-Chat,
+  author = {{MinSiThu}},
+  title = {MyanmarGPT-Chat},
+  url = {https://huggingface.co/jojo-ai-mst/MyanmarGPT-Chat},
+  urldate = {2024-1-28}
+  date = {2024-1-28},
+}
+```