Instructions to use saurabhin2it/Cats_LLM_in2it with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use saurabhin2it/Cats_LLM_in2it with PEFT:

from peft import PeftModel
from transformers import AutoModelForCausalLM

base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mistral-7B-Instruct-v0.2")
model = PeftModel.from_pretrained(base_model, "saurabhin2it/Cats_LLM_in2it")

Transformers

How to use saurabhin2it/Cats_LLM_in2it with Transformers:

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

pipe = pipeline("text-generation", model="saurabhin2it/Cats_LLM_in2it")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("saurabhin2it/Cats_LLM_in2it", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use saurabhin2it/Cats_LLM_in2it with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "saurabhin2it/Cats_LLM_in2it"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "saurabhin2it/Cats_LLM_in2it",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/saurabhin2it/Cats_LLM_in2it

SGLang

How to use saurabhin2it/Cats_LLM_in2it 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 "saurabhin2it/Cats_LLM_in2it" \
    --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": "saurabhin2it/Cats_LLM_in2it",
		"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 "saurabhin2it/Cats_LLM_in2it" \
        --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": "saurabhin2it/Cats_LLM_in2it",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use saurabhin2it/Cats_LLM_in2it with Docker Model Runner:
```
docker model run hf.co/saurabhin2it/Cats_LLM_in2it
```

Cats_LLM_in2it / tokenizer_config.json

saurabhin2it

Upload folder using huggingface_hub

fc1259f verified about 1 year ago

Raw

History Blame Contribute Delete

2.26 kB

	{
	"add_bos_token": true,
	"add_eos_token": false,
	"add_prefix_space": null,
	"added_tokens_decoder": {
	"0": {
	"content": "<unk>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"1": {
	"content": "<s>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"2": {
	"content": "</s>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"32000": {
	"content": "<\|tool_code\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"32001": {
	"content": "<\|tool_response\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"32002": {
	"content": "<\|user_message\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"32003": {
	"content": "<\|assistant_message\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	},
	"32004": {
	"content": "<\|system_message\|>",
	"lstrip": false,
	"normalized": false,
	"rstrip": false,
	"single_word": false,
	"special": true
	}
	},
	"additional_special_tokens": [
	"<\|tool_code\|>",
	"<\|tool_response\|>",
	"<\|user_message\|>",
	"<\|assistant_message\|>",
	"<\|system_message\|>"
	],
	"bos_token": "<s>",
	"clean_up_tokenization_spaces": false,
	"eos_token": "</s>",
	"extra_special_tokens": {},
	"legacy": false,
	"max_length": 512,
	"model_max_length": 1000000000000000019884624838656,
	"pad_to_multiple_of": null,
	"pad_token": "</s>",
	"pad_token_type_id": 0,
	"padding_side": "left",
	"sp_model_kwargs": {},
	"spaces_between_special_tokens": false,
	"stride": 0,
	"tokenizer_class": "LlamaTokenizer",
	"truncation_side": "right",
	"truncation_strategy": "longest_first",
	"unk_token": "<unk>",
	"use_default_system_prompt": false
	}