Instructions to use anktechsol/ankiGPT-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use anktechsol/ankiGPT-small with Transformers:

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

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

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("anktechsol/ankiGPT-small")
model = AutoModelForCausalLM.from_pretrained("anktechsol/ankiGPT-small", device_map="auto")
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 anktechsol/ankiGPT-small with vLLM:

Install from pip and serve model

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

Use Docker

docker model run hf.co/anktechsol/ankiGPT-small

SGLang

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

Docker Model Runner
How to use anktechsol/ankiGPT-small with Docker Model Runner:
```
docker model run hf.co/anktechsol/ankiGPT-small
```

anktechsol commited on Aug 25, 2025

Commit

b8f1a1c

verified ·

1 Parent(s): 96f6f5c

Update README.md

Browse files

Files changed (1) hide show

README.md +42 -30

README.md CHANGED Viewed

@@ -13,53 +13,65 @@ library_name: transformers
 tags:
 - text-generation-inference
 ---
-# Model Card for AnkiGPT-small
-## Model Details
-### Model Description
-- **Developed by:** [anktechsol.com](www.anktechsol.com)
-- **Shared by:** [anktechsol]
-- **Model type:** Causal Language Model
-- **Language(s) (NLP):** English, potentially aspects of Indian languages/Hinglish due to fine-tuning data.
- **Finetuned from model:** `microsoft/DialoGPT-small`
-### Model Sources
-- **Repository:** `https://huggingface.co/anktechsol/ankiGPT-small`
-## Uses
-### Direct Use
-This model can be used for text generation, particularly in conversational or narrative contexts, with a potential bias towards topics and linguistic styles present in the fine-tuning dataset (Indian conversational data).
-### Downstream Use
-This model could potentially be used as a base for further fine-tuning on more specific Indian language tasks or domains.
-### Out-of-Scope Use
-This model is not suitable for generating factual information, performing critical tasks requiring high accuracy, or deployment in sensitive applications without extensive further evaluation and mitigation of potential biases.
-## Bias, Risks, and Limitations
-Based on initial testing, the model may exhibit repetitive text generation, especially for longer sequences. The model's knowledge and linguistic style are heavily influenced by the fine-tuning dataset, which may not cover all aspects of Indian languages or culture comprehensively. Biases present in the training data may be reflected in the model's output.
-### Recommendations
-Users should be aware of the model's limitations in generating coherent long text and potential biases. It is recommended to experiment with different generation parameters (`max_length`, `no_repeat_ngram_size`, sampling strategies) to improve output quality. For any critical applications, thorough testing and human review of generated content are essential.
-## How to Get Started with the Model
-Use the code below to get started with the model using the transformers library.
-```python
-from transformers import pipeline
-generator = pipeline("text-generation", model="anktechsol/ankiGPT-small")
-prompt = "Write a short story about a day in the life of a student in a bustling Indian city, describing their commute, interactions at school, and a cultural event they attend in the evening."
-generated_text = generator(prompt, max_length=300, num_return_sequences=1)
-print(generated_text[0]['generated_text'])
-```

 tags:
 - text-generation-inference
 ---
+# anktechsol/ankiGPT-small
+## 🧠 What is ankiGPT-small?
+A conversational **text-generation** model fine-tuned from `microsoft/DialoGPT-small` for Indian scenarios—supporting English and Hinglish. Use it to generate stories, dialogue, quick responses, and creative text.
+---
+## 🚀 Quick Start
+```python
+from transformers import pipeline
+generator = pipeline("text-generation", model="anktechsol/ankiGPT-small")
+prompt = "Write a short story about a day in the life of a student in a bustling Indian city."
+result = generator(prompt, max_length=300, num_return_sequences=1)
+print(result[0]['generated_text'])
+```
+*Copy-paste this code to see instant results!*
+---
+## ✨ Features
+- **Conversational:** Tuned for chat, stories, and messages
+- **Language:** English + Hinglish (Indian conversational flavor)
+- **Base Model:** DialoGPT-small
+- **Size:** 124M parameters (fast and lightweight)
+- **Dataset:** ai4bharat/indic-align (Indian context data)
+---
+## 💡 Example Outputs
+> **Prompt:** "Describe the Diwali celebrations in Mumbai."
+>
+> **Output:** "The city sparkled with thousands of lights, families prepared delicious sweets, and friends gathered for bursting crackers, laughter echoing through the alleys."
+>
+> *Try your own prompts above!*
+---
+## ⚠️ Limitations & Considerations
+- Tends to repeat on long text—adjust `max_length` and `no_repeat_ngram_size` as needed
+- Biased towards Indian contexts due to training data
+- Not for critical or factual information generation
+---
+## 🙌 Contributions & Community
+- **Suggestions?** Open an issue or start a discussion. We welcome community feedback!
+- **Demo:** Want a hands-on demo? Let us know!
+---
+## 🔗 References
+- [anktechsol.com](https://www.anktechsol.com)
+---