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Remek
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Remek
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Remek/basal-1.0-4.5B
Input Modalities
Output Modalities
Supported Functionality
1. Install into a fresh uv environment (no git needed):
bash
uv venv --python 3.12 ~/basal-vllm && source ~/basal-vllm/bin/activateuv pip install "basal[vllm] @ https://github.com/rkinas/basal/archive/refs/tags/v1.0.1.tar.gz"A separate environment: vLLM installs its own torch. FP8 runs on Hopper and Blackwell GPUs.
2. Start the server and wait until it prints basal: model ... ready:
bash
basal-serve --model Remek/basal-1.0-4.5B-FP8 --mode vllm --port 8000vLLM loads the checkpoint and captures its graphs on the first start.
3. Ask a question (in a second terminal):
bash
curl -s localhost:8000/v1/systemone -H 'content-type: application/json' -d '{ "state": "Klient: od wczoraj nie mogę zalogować się do bankowości internetowej.", "questions": {"dept": {"type": "choice", "instructions": "Do którego działu skierować zgłoszenie?", "criteria": {"cards": "Reklamacje kart", "online": "Wsparcie bankowości elektronicznej", "loans": "Kredyty"}}}}'The response has a calibrated probability for every option, the chosen key and the confidence:
json
{"model": "basal-1.0-4.5B-FP8", "answers": {"dept": {"type": "choice", "choice": "online", "probabilities": {"cards": …, "online": …, "loans": …}, "confidence": …}}, "usage": {"input_tokens": …, "output_tokens": 0, "questions": 1, "latency_ms": …}}From Python (the basal package includes a client):
python
from basal.client import Basalb = Basal("http://127.0.0.1:8000")state = "Klient: od wczoraj nie mogę zalogować się do bankowości internetowej."a = b.choice(state, "Do którego działu skierować zgłoszenie?", {"cards": "Reklamacje kart", "online": "Wsparcie bankowości elektronicznej", "loans": "Kredyty"})print(a["choice"], a["confidence"]) # chosen key and its probabilityprint(b.yes_no(state, "Czy klient zgłasza problem techniczny?")["noul"]) # P(yes)print(b.score(state, "Jak pilne jest zgłoszenie?", ["niska", "średnia", "wysoka"])["score"]) # expected level 0-2Many items at once: basal-run --input items.jsonl --output answers.jsonl
(JSONL format). Several questions per request, option keys, early exit and the
full response format: API.
bibtex
@techreport{kinas2026basal, title = {basal-1.0: Reliable, Highly Optimized Typed Decisions for Polish}, author = {Kinas, Remigiusz}, institution = {ai5}, year = {2026}, type = {Technical report}, doi = {10.5281/zenodo.23022986}, url = {https://doi.org/10.5281/zenodo.23022986}}uv venv --python 3.12 ~/basal-vllm && source ~/basal-vllm/bin/activateuv pip install "basal[vllm] @ https://github.com/rkinas/basal/archive/refs/tags/v1.0.1.tar.gz"basal-serve --model Remek/basal-1.0-4.5B-FP8 --mode vllm --port 8000curl -s localhost:8000/v1/systemone -H 'content-type: application/json' -d '{ "state": "Klient: od wczoraj nie mogę zalogować się do bankowości internetowej.", "questions": {"dept": {"type": "choice", "instructions": "Do którego działu skierować zgłoszenie?", "criteria": {"cards": "Reklamacje kart", "online": "Wsparcie bankowości elektronicznej", "loans": "Kredyty"}}}}'from basal.client import Basalb = Basal("http://127.0.0.1:8000")state = "Klient: od wczoraj nie mogę zalogować się do bankowości internetowej."a = b.choice(state, "Do którego działu skierować zgłoszenie?", {"cards": "Reklamacje kart", "online": "Wsparcie bankowości elektronicznej", "loans": "Kredyty"})print(a["choice"], a["confidence"]) # chosen key and its probabilityprint(b.yes_no(state, "Czy klient zgłasza problem techniczny?")["noul"]) # P(yes)print(b.score(state, "Jak pilne jest zgłoszenie?", ["niska", "średnia", "wysoka"])["score"]) # expected level 0-2@techreport{kinas2026basal, title = {basal-1.0: Reliable, Highly Optimized Typed Decisions for Polish}, author = {Kinas, Remigiusz}, institution = {ai5}, year = {2026}, type = {Technical report}, doi = {10.5281/zenodo.23022986}, url = {https://doi.org/10.5281/zenodo.23022986}}{"model": "basal-1.0-4.5B-FP8", "answers": {"dept": {"type": "choice", "choice": "online", "probabilities": {"cards": …, "online": …, "loans": …}, "confidence": …}}, "usage": {"input_tokens": …, "output_tokens": 0, "questions": 1, "latency_ms": …}}