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

Libraries

How to use jinymusim/dialogmodel with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("jinymusim/dialogmodel")
model = AutoModelForCausalLM.from_pretrained("jinymusim/dialogmodel")

Notebooks
Google Colab
Kaggle
Local Apps

vLLM

How to use jinymusim/dialogmodel with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/jinymusim/dialogmodel

SGLang

How to use jinymusim/dialogmodel 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 "jinymusim/dialogmodel" \
    --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": "jinymusim/dialogmodel",
		"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 "jinymusim/dialogmodel" \
        --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": "jinymusim/dialogmodel",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use jinymusim/dialogmodel with Docker Model Runner:
```
docker model run hf.co/jinymusim/dialogmodel
```
Browse Quantizations to use this model in llama.cpp, Ollama, LM Studio, or any compatible app.

Useless ChitChat Language Model

Basic Dialog Model from DialoGPT-small. Finetuned on Dialog dataset. (Daily Dialog, MultiWoz)

For better usage. Use repo https://github.com/jinymusim/Daily-Dialog-GPT

How to use

If used with repo https://github.com/jinymusim/Daily-Dialog-GPT
User only needs to start the ds.py script. Otherwise use following

Use it as any torch python Language Model

from transformers import AutoModelForCausalLM, AutoTokenizer
import torch

tokenizer = AutoTokenizer.from_pretrained("jinymusim/dialogmodel")
model = AutoModelForCausalLM.from_pretrained("jinymusim/dialogmodel")

# Take user Input
user_utterance = input('USER> ')
user_utterance = user_utterance.strip()
tokenized_context = tokenizer.encode(user_utterance + tokenizer.eos_token, return_tensors='pt')

# generated a response, limit max_lenght to resonable size 
out_response = model.generate(tokenized_context, 
                                max_length=100,
                                num_beams=2,
                                no_repeat_ngram_size=2,
                                early_stopping=True,
                                pad_token_id=self.tokenizer.eos_token_id)

# Truncate User Input
decoded_response = self.tokenizer.decode(out_response[0], skip_special_tokens=True)[len(user_utterance):]

print(f'SYSTEM> {decoded_response}')

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Safetensors

Model size

0.1B params

Tensor type

F32

Model tree for jinymusim/dialogmodel

Quantizations

2 models

jinymusim
/

dialogmodel

Useless ChitChat Language Model

How to use

Model tree for jinymusim/dialogmodel

Datasets used to train jinymusim/dialogmodel