Text Generation
Transformers
Safetensors
English
llama
small
cpu
supra
tiny
mini
open
open-source
Eval Results (legacy)
text-generation-inference
Instructions to use SupraLabs/Supra-Mini-0.1M with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SupraLabs/Supra-Mini-0.1M with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="SupraLabs/Supra-Mini-0.1M")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("SupraLabs/Supra-Mini-0.1M") model = AutoModelForCausalLM.from_pretrained("SupraLabs/Supra-Mini-0.1M") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use SupraLabs/Supra-Mini-0.1M with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SupraLabs/Supra-Mini-0.1M" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SupraLabs/Supra-Mini-0.1M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/SupraLabs/Supra-Mini-0.1M
- SGLang
How to use SupraLabs/Supra-Mini-0.1M 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/Supra-Mini-0.1M" \ --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/Supra-Mini-0.1M", "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/Supra-Mini-0.1M" \ --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/Supra-Mini-0.1M", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use SupraLabs/Supra-Mini-0.1M with Docker Model Runner:
docker model run hf.co/SupraLabs/Supra-Mini-0.1M
| | Tasks |Version|Filter|n-shot| Metric | | Value | |Stderr| | |
| |------------------------------------------------------------|------:|------|-----:|---------------|---|------------:|---|------| | |
| |blimp | 2|none | 0|acc |↑ | 0.5177|± |0.0017| | |
| | - blimp_adjunct_island | 1|none | 0|acc |↑ | 0.7430|± |0.0138| | |
| | - blimp_anaphor_gender_agreement | 1|none | 0|acc |↑ | 0.2600|± |0.0139| | |
| | - blimp_anaphor_number_agreement | 1|none | 0|acc |↑ | 0.4650|± |0.0158| | |
| | - blimp_animate_subject_passive | 1|none | 0|acc |↑ | 0.5740|± |0.0156| | |
| | - blimp_animate_subject_trans | 1|none | 0|acc |↑ | 0.6820|± |0.0147| | |
| | - blimp_causative | 1|none | 0|acc |↑ | 0.4270|± |0.0156| | |
| | - blimp_complex_NP_island | 1|none | 0|acc |↑ | 0.4380|± |0.0157| | |
| | - blimp_coordinate_structure_constraint_complex_left_branch| 1|none | 0|acc |↑ | 0.0860|± |0.0089| | |
| | - blimp_coordinate_structure_constraint_object_extraction | 1|none | 0|acc |↑ | 0.5060|± |0.0158| | |
| | - blimp_determiner_noun_agreement_1 | 1|none | 0|acc |↑ | 0.5960|± |0.0155| | |
| | - blimp_determiner_noun_agreement_2 | 1|none | 0|acc |↑ | 0.5470|± |0.0157| | |
| | - blimp_determiner_noun_agreement_irregular_1 | 1|none | 0|acc |↑ | 0.5110|± |0.0158| | |
| | - blimp_determiner_noun_agreement_irregular_2 | 1|none | 0|acc |↑ | 0.5840|± |0.0156| | |
| | - blimp_determiner_noun_agreement_with_adj_2 | 1|none | 0|acc |↑ | 0.4880|± |0.0158| | |
| | - blimp_determiner_noun_agreement_with_adj_irregular_1 | 1|none | 0|acc |↑ | 0.4500|± |0.0157| | |
| | - blimp_determiner_noun_agreement_with_adj_irregular_2 | 1|none | 0|acc |↑ | 0.5310|± |0.0158| | |
| | - blimp_determiner_noun_agreement_with_adjective_1 | 1|none | 0|acc |↑ | 0.5190|± |0.0158| | |
| | - blimp_distractor_agreement_relational_noun | 1|none | 0|acc |↑ | 0.3480|± |0.0151| | |
| | - blimp_distractor_agreement_relative_clause | 1|none | 0|acc |↑ | 0.3440|± |0.0150| | |
| | - blimp_drop_argument | 1|none | 0|acc |↑ | 0.7320|± |0.0140| | |
| | - blimp_ellipsis_n_bar_1 | 1|none | 0|acc |↑ | 0.2240|± |0.0132| | |
| | - blimp_ellipsis_n_bar_2 | 1|none | 0|acc |↑ | 0.2920|± |0.0144| | |
| | - blimp_existential_there_object_raising | 1|none | 0|acc |↑ | 0.7300|± |0.0140| | |
| | - blimp_existential_there_quantifiers_1 | 1|none | 0|acc |↑ | 0.7110|± |0.0143| | |
| | - blimp_existential_there_quantifiers_2 | 1|none | 0|acc |↑ | 0.0400|± |0.0062| | |
| | - blimp_existential_there_subject_raising | 1|none | 0|acc |↑ | 0.6460|± |0.0151| | |
| | - blimp_expletive_it_object_raising | 1|none | 0|acc |↑ | 0.6440|± |0.0151| | |
| | - blimp_inchoative | 1|none | 0|acc |↑ | 0.3790|± |0.0153| | |
| | - blimp_intransitive | 1|none | 0|acc |↑ | 0.5630|± |0.0157| | |
| | - blimp_irregular_past_participle_adjectives | 1|none | 0|acc |↑ | 0.4000|± |0.0155| | |
| | - blimp_irregular_past_participle_verbs | 1|none | 0|acc |↑ | 0.5430|± |0.0158| | |
| | - blimp_irregular_plural_subject_verb_agreement_1 | 1|none | 0|acc |↑ | 0.4460|± |0.0157| | |
| | - blimp_irregular_plural_subject_verb_agreement_2 | 1|none | 0|acc |↑ | 0.5100|± |0.0158| | |
| | - blimp_left_branch_island_echo_question | 1|none | 0|acc |↑ | 0.8390|± |0.0116| | |
| | - blimp_left_branch_island_simple_question | 1|none | 0|acc |↑ | 0.1170|± |0.0102| | |
| | - blimp_matrix_question_npi_licensor_present | 1|none | 0|acc |↑ | 0.0020|± |0.0014| | |
| | - blimp_npi_present_1 | 1|none | 0|acc |↑ | 0.5060|± |0.0158| | |
| | - blimp_npi_present_2 | 1|none | 0|acc |↑ | 0.5070|± |0.0158| | |
| | - blimp_only_npi_licensor_present | 1|none | 0|acc |↑ | 0.1620|± |0.0117| | |
| | - blimp_only_npi_scope | 1|none | 0|acc |↑ | 0.0930|± |0.0092| | |
| | - blimp_passive_1 | 1|none | 0|acc |↑ | 0.5950|± |0.0155| | |
| | - blimp_passive_2 | 1|none | 0|acc |↑ | 0.6130|± |0.0154| | |
| | - blimp_principle_A_c_command | 1|none | 0|acc |↑ | 0.5840|± |0.0156| | |
| | - blimp_principle_A_case_1 | 1|none | 0|acc |↑ | 0.9990|± |0.0010| | |
| | - blimp_principle_A_case_2 | 1|none | 0|acc |↑ | 0.4280|± |0.0157| | |
| | - blimp_principle_A_domain_1 | 1|none | 0|acc |↑ | 1.0000|± | 0| | |
| | - blimp_principle_A_domain_2 | 1|none | 0|acc |↑ | 0.6010|± |0.0155| | |
| | - blimp_principle_A_domain_3 | 1|none | 0|acc |↑ | 0.5150|± |0.0158| | |
| | - blimp_principle_A_reconstruction | 1|none | 0|acc |↑ | 0.1900|± |0.0124| | |
| | - blimp_regular_plural_subject_verb_agreement_1 | 1|none | 0|acc |↑ | 0.6880|± |0.0147| | |
| | - blimp_regular_plural_subject_verb_agreement_2 | 1|none | 0|acc |↑ | 0.5920|± |0.0155| | |
| | - blimp_sentential_negation_npi_licensor_present | 1|none | 0|acc |↑ | 0.9990|± |0.0010| | |
| | - blimp_sentential_negation_npi_scope | 1|none | 0|acc |↑ | 0.5420|± |0.0158| | |
| | - blimp_sentential_subject_island | 1|none | 0|acc |↑ | 0.3570|± |0.0152| | |
| | - blimp_superlative_quantifiers_1 | 1|none | 0|acc |↑ | 0.4970|± |0.0158| | |
| | - blimp_superlative_quantifiers_2 | 1|none | 0|acc |↑ | 0.6980|± |0.0145| | |
| | - blimp_tough_vs_raising_1 | 1|none | 0|acc |↑ | 0.2810|± |0.0142| | |
| | - blimp_tough_vs_raising_2 | 1|none | 0|acc |↑ | 0.7660|± |0.0134| | |
| | - blimp_transitive | 1|none | 0|acc |↑ | 0.6110|± |0.0154| | |
| | - blimp_wh_island | 1|none | 0|acc |↑ | 0.2680|± |0.0140| | |
| | - blimp_wh_questions_object_gap | 1|none | 0|acc |↑ | 0.7850|± |0.0130| | |
| | - blimp_wh_questions_subject_gap | 1|none | 0|acc |↑ | 0.9600|± |0.0062| | |
| | - blimp_wh_questions_subject_gap_long_distance | 1|none | 0|acc |↑ | 0.9490|± |0.0070| | |
| | - blimp_wh_vs_that_no_gap | 1|none | 0|acc |↑ | 0.9830|± |0.0041| | |
| | - blimp_wh_vs_that_no_gap_long_distance | 1|none | 0|acc |↑ | 0.9770|± |0.0047| | |
| | - blimp_wh_vs_that_with_gap | 1|none | 0|acc |↑ | 0.0070|± |0.0026| | |
| | - blimp_wh_vs_that_with_gap_long_distance | 1|none | 0|acc |↑ | 0.0190|± |0.0043| | |
| |arc_easy | 1|none | 0|acc |↑ | 0.2639|± |0.0090| | |
| | | |none | 0|acc_norm |↑ | 0.2731|± |0.0091| | |
| |wikitext | 2|none | 0|bits_per_byte |↓ | 4.6536|± | N/A| | |
| | | |none | 0|byte_perplexity|↓ | 25.1691|± | N/A| | |
| | | |none | 0|word_perplexity|↓ |30979484.4095|± | N/A| | |
| |Groups|Version|Filter|n-shot|Metric| |Value | |Stderr| | |
| |------|------:|------|-----:|------|---|-----:|---|-----:| | |
| |blimp | 2|none | 0|acc |↑ |0.5177|± |0.0017| |