Instructions to use TechxGenus/CursorCore-DS-1.3B-GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use TechxGenus/CursorCore-DS-1.3B-GPTQ with Transformers:

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

pipe = pipeline("text-generation", model="TechxGenus/CursorCore-DS-1.3B-GPTQ")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("TechxGenus/CursorCore-DS-1.3B-GPTQ")
model = AutoModelForCausalLM.from_pretrained("TechxGenus/CursorCore-DS-1.3B-GPTQ")
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

vLLM

How to use TechxGenus/CursorCore-DS-1.3B-GPTQ with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "TechxGenus/CursorCore-DS-1.3B-GPTQ"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "TechxGenus/CursorCore-DS-1.3B-GPTQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/TechxGenus/CursorCore-DS-1.3B-GPTQ

SGLang

How to use TechxGenus/CursorCore-DS-1.3B-GPTQ 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 "TechxGenus/CursorCore-DS-1.3B-GPTQ" \
    --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": "TechxGenus/CursorCore-DS-1.3B-GPTQ",
		"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 "TechxGenus/CursorCore-DS-1.3B-GPTQ" \
        --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": "TechxGenus/CursorCore-DS-1.3B-GPTQ",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use TechxGenus/CursorCore-DS-1.3B-GPTQ with Docker Model Runner:
```
docker model run hf.co/TechxGenus/CursorCore-DS-1.3B-GPTQ
```

CursorCore-DS-1.3B-GPTQ / tokenizer_config.json

TechxGenus

Upload folder using huggingface_hub

8d1ae12 verified over 1 year ago

raw

history blame contribute delete

7.7 kB

	{
	"add_bos_token": true,
	"add_eos_token": false,
	"add_prefix_space": null,
	"added_tokens_decoder": {
	"32000": {
	"content": "õ",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32001": {
	"content": "÷",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32002": {
	"content": "Á",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32003": {
	"content": "ý",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32004": {
	"content": "À",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32005": {
	"content": "ÿ",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32006": {
	"content": "ø",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32007": {
	"content": "ú",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32008": {
	"content": "þ",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32009": {
	"content": "ü",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32010": {
	"content": "ù",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32011": {
	"content": "ö",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32012": {
	"content": "û",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32013": {
	"content": "<｜begin▁of▁sentence｜>",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"32014": {
	"content": "<｜end▁of▁sentence｜>",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"32015": {
	"content": "<｜fim▁hole｜>",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32016": {
	"content": "<｜fim▁begin｜>",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32017": {
	"content": "<｜fim▁end｜>",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32018": {
	"content": "<pad>",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32019": {
	"content": "<\|User\|>",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32020": {
	"content": "<\|Assistant\|>",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32021": {
	"content": "<\|EOT\|>",
	"lstrip": false,
	"normalized": true,
	"rstrip": false,
	"single_word": false,
	"special": false
	},
	"32022": {
	"content": "<\|im_end\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"32023": {
	"content": "<\|im_start\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"32024": {
	"content": "<\|next_start\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"32025": {
	"content": "<\|next_end\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"32026": {
	"content": "<\|target_start\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"32027": {
	"content": "<\|target_end\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"32028": {
	"content": "<\|target\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"32029": {
	"content": "<\|search_and_replace\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	}
	},
	"additional_special_tokens": [
	"<\|im_start\|>",
	"<\|im_end\|>",
	"<\|next_start\|>",
	"<\|next_end\|>",
	"<\|target_start\|>",
	"<\|target_end\|>",
	"<\|target\|>",
	"<\|search_and_replace\|>"
	],
	"bos_token": "<｜begin▁of▁sentence｜>",
	"chat_template": [
	{
	"name": "default",
	"template": "{% for message in messages %}{% if loop.first and message['role'] != 'system' %}{{ '<\|im_start\|>system\nYou are a helpful programming assistant.<\|im_end\|>\n' }}{% endif %}{% if not loop.first %}{{ '\n' }}{% endif %}{{ '<\|im_start\|>' + message['role'] }}{% if 'name' in message %}{{ ' name=' + message['name'] }}{% endif %}{{ '\n' + message['content'] + '<\|im_end\|>' }}{% if loop.last and add_generation_prompt %}{{ '\n<\|im_start\|>assistant\n' }}{% endif %}{% endfor %}"
	},
	{
	"name": "assistant-conversation",
	"template": "{% for message in messages %}{% if loop.first and message['role'] != 'system' %}{{ '<\|im_start\|>system\nYou are a helpful programming assistant.<\|im_end\|>\n' }}{% endif %}{% if not loop.first %}{{ '\n' }}{% endif %}{{ '<\|im_start\|>' + message['role'] }}{% if 'name' in message %}{{ ' name=' + message['name'] }}{% endif %}{{ '\n' + message['content'] + '<\|im_end\|>' }}{% if loop.last and add_generation_prompt %}{{ '\n<\|im_start\|>assistant\n<\|next_start\|>' }}{% endif %}{% endfor %}"
	},
	{
	"name": "prefix_response",
	"template": "{% for message in messages %}{% if loop.first and message['role'] != 'system' %}{{ '<\|im_start\|>system\nYou are a helpful programming assistant.<\|im_end\|>\n' }}{% endif %}{% if not loop.first %}{{ '\n' }}{% endif %}{{ '<\|im_start\|>' + message['role'] }}{% if 'name' in message %}{{ ' name=' + message['name'] }}{% endif %}{{ '\n' + message['content'] }}{% if not loop.last %}{{ '<\|im_end\|>' }}{% endif %}{% endfor %}"
	}
	],
	"clean_up_tokenization_spaces": false,
	"eos_token": "<\|im_end\|>",
	"legacy": true,
	"max_length": 16384,
	"model_max_length": 16384,
	"pad_to_multiple_of": null,
	"pad_token": "<｜end▁of▁sentence｜>",
	"pad_token_type_id": 0,
	"padding_side": "left",
	"sp_model_kwargs": {},
	"stride": 0,
	"tokenizer_class": "LlamaTokenizer",
	"truncation_side": "right",
	"truncation_strategy": "longest_first",
	"unk_token": null,
	"use_default_system_prompt": false
	}