Text Generation
Transformers
Safetensors
English
llama
micro
nano
small
supra
SupraLabs
gtx
rtx
nvidia
lh-tech
axionlab
text-generation-inference
Instructions to use SupraLabs/MicroSupra-1k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SupraLabs/MicroSupra-1k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="SupraLabs/MicroSupra-1k")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("SupraLabs/MicroSupra-1k") model = AutoModelForCausalLM.from_pretrained("SupraLabs/MicroSupra-1k") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use SupraLabs/MicroSupra-1k with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SupraLabs/MicroSupra-1k" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SupraLabs/MicroSupra-1k", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SupraLabs/MicroSupra-1k
- SGLang
How to use SupraLabs/MicroSupra-1k 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 "SupraLabs/MicroSupra-1k" \ --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": "SupraLabs/MicroSupra-1k", "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 "SupraLabs/MicroSupra-1k" \ --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": "SupraLabs/MicroSupra-1k", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use SupraLabs/MicroSupra-1k with Docker Model Runner:
docker model run hf.co/SupraLabs/MicroSupra-1k
| license: mit | |
| datasets: | |
| - HuggingFaceFW/fineweb-edu | |
| language: | |
| - en | |
| pipeline_tag: text-generation | |
| tags: | |
| - micro | |
| - nano | |
| - small | |
| - supra | |
| - SupraLabs | |
| - gtx | |
| - rtx | |
| - nvidia | |
| - llama | |
| - lhtech | |
| - axionlab | |
| library_name: transformers | |
| ## **MicroSupra-1k** | |
| So... have you ever seen a model that runs on a 3 dollars hardware? No? If no, Now you're seeing! | |
| MicroSupra-1k is a 1k parameters model trained on 300M Tokens of FineWeb-Edu for 1 minute(Yes! 59 seconds!) on a GTX 750Ti 4GB(AxionLab Hardware) | |
| **Some model outputs:** | |
| [*] Prompt: The main concept of physics is | |
| [*] Output: The main concept of physics is a,s and the. thet to, theing.... the,a then,c,i to, thee in b. toed.,,e theyalp the in,er thees- s,el,,,, | |
| and, the of ine,,s the of cs of thesss the. f. to. thesining andor dar,,al the,. of p. | |
| the.s the.,,s. anded,e. of, ofed, l toinging and themsr the of of. to | |
| to thes thes aen,., ofes of a. | |
| [*] Prompt: My name is | |
| [*] Output: My name is ed and. as the, to. the, iningt thee the ofingi in | |
| the., anda.-eo | |
| ofles, b the,er,s fing.ssp the the | |
| , of of, the,al, d to the m, the, to toed, | |
| seng,,.y. in the,., in and them the thened.sing to | |
| the of of andan the the,, the | |
| to..,,sing,,.aring the the. of.al.,s ofcal ar s..e and.sssor of, and and. | |
| [*] Prompt: Question: What is the capital of France?\nAnswer: | |
| [*] Output: Question: What is the capital of France? | |
| Answer:,. and to the. toc. ofs the m,a thee.. the, f ofling. as.,,y bt, the p, in, the,,ees toed ing to.o, | |
| thes. the..,s the.ed and andang,,ed the of,,ms. of, thei the, the,ey,,s l.ing toe the the,se the to, the, the,aror, the of-. in the. the. the,e the of ds to,ic the the aal at the.. | |
| ingssy s and and | |
| **🚫What the model CAN'T do:** | |
| Think | |
| Chat | |
| even predict the next token correctly lol | |
| **Why SupraLabs created this???** | |
| Because we are experimenting sizes, experiments(like 1Bit quant, distillation(NEW THINGS ARE COMING WITH DISTILLATION! GET TUNED!), pruning, all to better your experience! We are working to big things!) | |
| **Final thought** | |
| Even without any intelligence, it shows that scaling laws are real. This ant model doesn't know how to talk, but we all know it emotions 🤖🫶 | |
| SupraLabs are excited to work at more things to you! |