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This PR fixes a bug in supporting OPT-350m/OPT-6.7b/OPT-13b and OPT-IML models.

The bug happened because our model code didn't include some methods that were required to tie the input and output embeddings.

@WoosukKwon WoosukKwon merged commit cbf8779 into main Feb 25, 2023
@WoosukKwon WoosukKwon deleted the fix-opt branch February 25, 2023 00:29
CZT0 referenced this pull request in semedia-tech/vllm Sep 11, 2023
orangetin referenced this pull request in togethercomputer/vllm-ttgi Sep 14, 2023
add rope scaling as a cli arg so openai server can load rope scaled models
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hongxiayang referenced this pull request in hongxiayang/vllm Feb 13, 2024
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Deterministic OpenVINO inference
daniel-geon-park added a commit to gmlwns2000/vllm-timber that referenced this pull request Apr 15, 2024
mzusman pushed a commit to mzusman/vllm that referenced this pull request Apr 16, 2024
BA-78554: Jurassic 2.5

* worked on jurasic2.5 configuration file, updated jurassic2_5 modeling file to support alternating experts/attn layers

* finished working the forward pass of jurassic3.py

* finished working the forward pass of jurassic3.py

* finished working the forward pass of jurassic3.py

* jurassic_3 modeling file works, uses dummy weights initialized by "dummy" flag. Tokenizer raises issues, for now copying the mixtral tokenizer

* changed default tokenizer vocab values, loading of custom .pt weight files works.

* removed notebook

* merging master to jurassic-2.5 to reset head

* Merge branch 'master' into jurassic-2.5

* align to master

Approved-by: Tomer Asida
Approved-by: Mor Zusman
Bellk17 added a commit to Bellk17/vllm that referenced this pull request May 10, 2024
ykim362 referenced this pull request in ykim362/vllm Jun 17, 2024
Group Gemm Version
yyu6969 pushed a commit to yyu6969/vllm that referenced this pull request Apr 22, 2025
heheda12345 added a commit that referenced this pull request May 23, 2025
bbartels pushed a commit to bbartels/vllm that referenced this pull request Aug 14, 2025
yuz207 added a commit to IluvatarLabs/vllm that referenced this pull request Sep 27, 2025
Bug vllm-project#1 (CRITICAL): Add missing begin() and stage() methods to KVWriteRouter
- Flash attention backend calls router.begin() and router.stage()
- KVWriteRouter only had write() and commit() methods
- Added begin() to store slot_mapping and initialize shadow buffer
- Added stage() to extract per-timestep slot and stage KV pairs
- Without these, no tokens were being staged → 0% acceptance rate

Bug vllm-project#2 (MODERATE): Fix bonus token counting in accepted_lens
- valid_sampled_token_ids includes [accepted_draft_tokens..., bonus_token]
- Previous: len([bonus]) = 1, incorrectly counted as 1 accepted draft token
- Fixed: Use max(0, len(seq) - 1) to exclude bonus token from count
- Now correctly reports 0 accepted when only bonus token is present

Files modified:
- vllm/v1/kv_cache/write_router.py: Added begin() and stage() methods
- vllm/v1/worker/gpu_model_runner.py: Fixed accepted_lens calculation
yuz207 added a commit to IluvatarLabs/vllm that referenced this pull request Sep 27, 2025
Bug vllm-project#1: EAGLE tree proposal returned zeros for draft_logprobs
- Root cause: When using topk for tree branching, code set draft_logp_list=None,
  then created zeros tensor as fallback (lines 850-851)
- Fix: Compute actual log-probs from logits using log_softmax + gather
- Applied at 2 locations: root level (lines 698-704) and tree levels (lines 839-846)

Bug vllm-project#2: Added diagnostic logging in rejection sampler
- Log draft_p (nonzero) min/med/max to detect zeros
- Log p_target min/med/max to detect degenerate softmax
- Helps identify if target logits are masked/filtered before sampling

Expected results after fix:
- draft_logp: -3.2/-1.6/-0.0 (real log-probs, all ≤ 0) instead of 0/0/0
- p_target: 1e-6/1e-3/0.7 (realistic distribution) instead of 1/1/1
- Acceptance rate: 30-70% instead of 0%

Files changed:
- vllm/v1/spec_decode/eagle.py: Fix draft_logp computation
- vllm/v1/sample/rejection_sampler.py: Add sanity logging
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