Instructions to use ethzanalytics/distilgpt2-tiny-conversational with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use ethzanalytics/distilgpt2-tiny-conversational with Transformers:

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

pipe = pipeline("text-generation", model="ethzanalytics/distilgpt2-tiny-conversational")

# pip install -U transformers accelerate
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("ethzanalytics/distilgpt2-tiny-conversational")
model = AutoModelForCausalLM.from_pretrained("ethzanalytics/distilgpt2-tiny-conversational", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use ethzanalytics/distilgpt2-tiny-conversational with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "ethzanalytics/distilgpt2-tiny-conversational"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "ethzanalytics/distilgpt2-tiny-conversational",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Use Docker

docker model run hf.co/ethzanalytics/distilgpt2-tiny-conversational

SGLang

How to use ethzanalytics/distilgpt2-tiny-conversational 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 "ethzanalytics/distilgpt2-tiny-conversational" \
    --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": "ethzanalytics/distilgpt2-tiny-conversational",
		"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 "ethzanalytics/distilgpt2-tiny-conversational" \
        --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": "ethzanalytics/distilgpt2-tiny-conversational",
		"prompt": "Once upon a time,",
		"max_tokens": 512,
		"temperature": 0.5
	}'

Docker Model Runner
How to use ethzanalytics/distilgpt2-tiny-conversational with Docker Model Runner:
```
docker model run hf.co/ethzanalytics/distilgpt2-tiny-conversational
```

Update README.md

by Aobangaming - opened Sep 20

base: refs/heads/main

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from: refs/pr/3

Discussion Files changed

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README.md +62 -27

README.md CHANGED Viewed

@@ -7,43 +7,78 @@ tags:
 - distilgpt2
 - gpt2
 - ai-msgbot
 widget:
-- text: "I know you're tired, but can we go for another walk this evening?\nperson beta:\n\n"
-  example_title: "walk"
-- text: "Have you done anything exciting lately?\nperson beta:\n\n"
-  example_title: "activities"
-- text: "hey - do you have a favorite grocery store around here?\nperson beta:\n\n"
-  example_title: "grocery"
-- text: "Can you take me for dinner somewhere nice this time?\nperson beta:\n\n"
-  example_title: "dinner"
-- text: "What's your favorite form of social media?\nperson beta:\n\n"
-  example_title: "social media"
-- text: "Hi, how are you?\nperson beta:\n\n"
-  example_title: "greeting"
-- text: "I am the best; my sister is the worst. What am I?\nperson beta:\n\n"
-  example_title: "sister"
-- text: "What do you call an alligator who's just had surgery to remove his left arm?\nperson beta:\n\n"
-  example_title: "alligator"
-- text: "A man walks into a bar and asks for a drink. The bartender asks for $10, and he pays him $1. What did he pay him with?\nperson beta:\n\n"
-  example_title: "dollar"
-- text: "What did I say was in the mailbox when it was actually in the cabinet?\nperson beta:\n\n"
-  example_title: "mailbox"
-- text: "My friend says that she knows every language, but she doesn't speak any of them.. what's wrong with her?\nperson beta:\n\n"
-  example_title: "language"
 inference:
   parameters:
     min_length: 2
     max_length: 64
     length_penalty: 0.7
     no_repeat_ngram_size: 2
-    do_sample: True
     top_p: 0.95
     top_k: 20
     temperature: 0.3
     repetition_penalty: 3.5
 ---
@@ -127,4 +162,4 @@ The following hyperparameters were used during training:
 - Transformers 4.16.1
 - Pytorch 1.10.0+cu111
-- Tokenizers 0.11.0

 - distilgpt2
 - gpt2
 - ai-msgbot
 widget:
+- text: |+
+    I know you're tired, but can we go for another walk this evening?
+    person beta:
+  example_title: walk
+- text: |+
+    Have you done anything exciting lately?
+    person beta:
+  example_title: activities
+- text: |+
+    hey - do you have a favorite grocery store around here?
+    person beta:
+  example_title: grocery
+- text: |+
+    Can you take me for dinner somewhere nice this time?
+    person beta:
+  example_title: dinner
+- text: |+
+    What's your favorite form of social media?
+    person beta:
+  example_title: social media
+- text: |+
+    Hi, how are you?
+    person beta:
+  example_title: greeting
+- text: |+
+    I am the best; my sister is the worst. What am I?
+    person beta:
+  example_title: sister
+- text: |+
+    What do you call an alligator who's just had surgery to remove his left arm?
+    person beta:
+  example_title: alligator
+- text: >+
+    A man walks into a bar and asks for a drink. The bartender asks for $10, and
+    he pays him $1. What did he pay him with?
+    person beta:
+  example_title: dollar
+- text: |+
+    What did I say was in the mailbox when it was actually in the cabinet?
+    person beta:
+  example_title: mailbox
+- text: >+
+    My friend says that she knows every language, but she doesn't speak any of
+    them.. what's wrong with her?
+    person beta:
+  example_title: language
 inference:
   parameters:
     min_length: 2
     max_length: 64
     length_penalty: 0.7
     no_repeat_ngram_size: 2
+    do_sample: true
     top_p: 0.95
     top_k: 20
     temperature: 0.3
     repetition_penalty: 3.5
+pipeline_tag: text-generation
 ---
 - Transformers 4.16.1
 - Pytorch 1.10.0+cu111
+- Tokenizers 0.11.0