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AI Models 85003

• GLM-5.3-MXFP4xFP8↗

  RedHatAI

• Alphacode-AI_-_AlphaMist7B-slr-v2-gguf↗

  RichardErkhov

• datatab_-_Yugo55A-GPT-gguf↗

  RichardErkhov

• georgesung_-_llama2_7b_chat_uncensored-gguf↗

  RichardErkhov

• ibm-granite_-_granite-34b-code-base-8k-gguf↗

  RichardErkhov

• OpenSafetyLab_-_MD-Judge-v0_2-internlm2_7b-gguf↗

  RichardErkhov

• resnet34-finetuned-scenario16↗

  RichardsonI

• synth_pop-acestep1.5-xl-v1↗

  ryanontheinside

• Bielik-4.5B-v3.0-Instruct-GGUF↗

  second-state

• MIDI-LLM_Llama-3.2-1B↗

  slseanwu

  The model extends Llama 3.2's vocabulary (128,256 tokens) with 55,030 MIDI tokens representing: - **Onset time** (when notes occur) - **Durations** (how long each note is held) - **Instrument-pitch pair** (which note to play & by which instrument) These tokens follow the vocabulary of Anticipatory Music Transformer (AMT) (Thickstun et al., TMLR 2024). This model checkpoint was evaluated with **FAD** and **CLAP** metrics on 896 LakhMIDI examples whose IDs can be found in our repo - https://github.com/slSeanWU/MIDI-LLM/blob/main/assets/evaluation_set_lakh_ids.txt | Model | Params | Precision | FAD ↓ | CLAP ↑ | |-------|--------|-----------|-------|--------| | **MIDI-LLM** | 1.47B | BF16 | **0.173** | **22.1** | | **MIDI-LLM** | 1.47B | FP8 | 0.216 | 21.8 |