Instructions to use SZLHOLDINGS/chaski-r2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use SZLHOLDINGS/chaski-r2 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-0.8B") model = PeftModel.from_pretrained(base_model, "SZLHOLDINGS/chaski-r2") - Transformers
How to use SZLHOLDINGS/chaski-r2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="SZLHOLDINGS/chaski-r2") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("SZLHOLDINGS/chaski-r2") model = AutoModelForCausalLM.from_pretrained("SZLHOLDINGS/chaski-r2", device_map="auto") 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=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use SZLHOLDINGS/chaski-r2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "SZLHOLDINGS/chaski-r2" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "SZLHOLDINGS/chaski-r2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/SZLHOLDINGS/chaski-r2
- SGLang
How to use SZLHOLDINGS/chaski-r2 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 "SZLHOLDINGS/chaski-r2" \ --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": "SZLHOLDINGS/chaski-r2", "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 "SZLHOLDINGS/chaski-r2" \ --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": "SZLHOLDINGS/chaski-r2", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Unsloth Desktop
- Docker Model Runner
How to use SZLHOLDINGS/chaski-r2 with Docker Model Runner:
docker model run hf.co/SZLHOLDINGS/chaski-r2
docs: clarify chaski-r2 evidence and release boundary
Clarify the artifact's evidence and release boundary using the published records at base 4ef29684c56de07626b1cefb4b93a1b486de2aa1. The README now separates measured scope, historical failures, artifact binding, and authority limits. This PR changes README.md only.
Validation: YAML parsed; repository-relative links checked; Python snippets parsed where present; git diff --check passed. Source evidence and canonical references were inspected at immutable revisions. Local branch: docs/evidence-boundary-chaski-r2; local documentation commit: ae437c8587d2933294ea1baa232a9f4369a9fa31.
Evidence boundary checklist
- No weights, adapters, GGUFs, configs, datasets, licenses, or permissions changed.
- No evaluation receipt, metric, source hash, or authority state changed.
- Existing publication and autonomy boundaries preserved.
- No new deployment, benchmark, safety, or autonomy claim introduced.
- Numeric claims cite published records and retain their limits.
- Failures, missing bindings, unsigned status, and HOLD results remain visible where applicable.
Evidence reviewed
- https://github.com/szl-holdings/szl-forge/blob/a6b58f623185820eddfb0b279d21b7d81b87137c/chaski-r2/card/README.md
- https://github.com/szl-holdings/szl-forge/blob/a6b58f623185820eddfb0b279d21b7d81b87137c/frontier/evaluation/gate_runs/chaski-r2_4ef29684c56d_20260915T093042Z_receipt.json
- https://huggingface.co/SZLHOLDINGS/chaski-r2/blob/4ef29684c56de07626b1cefb4b93a1b486de2aa1/adapter-unsloth/training_receipt.json
- https://huggingface.co/SZLHOLDINGS/chaski-r2/blob/4ef29684c56de07626b1cefb4b93a1b486de2aa1/eval_merged_measured.json
- https://huggingface.co/SZLHOLDINGS/chaski-r2/blob/4ef29684c56de07626b1cefb4b93a1b486de2aa1/eval_named_n_generate.json
- https://huggingface.co/SZLHOLDINGS/chaski-r2/blob/4ef29684c56de07626b1cefb4b93a1b486de2aa1/merge_receipt.json
- https://huggingface.co/SZLHOLDINGS/chaski-r2/blob/4ef29684c56de07626b1cefb4b93a1b486de2aa1/provenance.json
- https://huggingface.co/SZLHOLDINGS/chaski-r2/blob/4ef29684c56de07626b1cefb4b93a1b486de2aa1/szl-source-binding.json
- https://huggingface.co/SZLHOLDINGS/chaski-r2/blob/4ef29684c56de07626b1cefb4b93a1b486de2aa1/training_receipt.json
- https://huggingface.co/SZLHOLDINGS/chaski-r2/blob/4ef29684c56de07626b1cefb4b93a1b486de2aa1/training_receipt.local.json
Signed-off-by: Lutar, Stephen P. stephenlutar2@gmail.com