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tenosra/longchat-7b-starkv-proxima
longchat-7b-starkv-proxima is a text generation model from tenosra. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as llama2.
STAR-KV checkpoint: lmsys/longchat-7b-v1.5-32k with attention K/V weights calibrated + fused into a low-rank form for KV-cache compression, produced by proximavllm (STAR-KV method).
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From the Hugging Face model README
STAR-KV checkpoint: lmsys/longchat-7b-v1.5-32k with attention K/V weights calibrated + fused into a low-rank form for KV-cache compression, produced by proxima_vllm (STAR-KV method).
Standard LongChat weights, plus a star_kv/ directory: weights.safetensors (fused low-rank K/V projections) and star_kv_config.json. config.json architecture set to ProximaStarKVLlamaForCausalLM. Directory loads directly as vLLM model= argument via additional_config.proxima_vllm.checkpoint.
lmsys/longchat-7b-v1.5-32kmax_rank_k=64, max_rank_v=64, sharpness=10.0, mixed-precision fusion (top_fraction=0.25, top_bits=4, bottom_bits=3)HuggingFaceFW/fineweb-edu (CC-MAIN-2013-20 shard)balanced (gamma=1e-3); aggressive (gamma=5e-3) and conservative (gamma=2e-4) profiles also independently calibrated and included in checkpointDeviation from paper (disclosed): paper calibrates on 3000 FineWeb-Edu samples x 2048 tokens (~6 GPU-hours, 8B model). This checkpoint uses a scaled-down real-(not-synthetic)-text run (~1/50th token volume) for single-session feasibility on one L4 GPU. Results should be read with that caveat — this is not a paper-scale calibration.
End-to-end vs plain vLLM (post-prefill-kernel-fix, 2026-08-06):
gpu_memory_utilization=0.83, not 0.85)Kernel-level:
from vllm import LLM
llm = LLM(
model="tenosra/longchat-7b-starkv-proxima",
additional_config={"proxima_vllm": {"checkpoint": True}},
)
Research checkpoint for benchmarking KV-cache compression at long context. Calibration sample count is far below the paper's protocol (see deviation note above) — treat compression/quality tradeoff numbers as directional, not final.