diff --git a/.github/ci/benchmark_config.json b/.github/ci/benchmark_config.json index 43f8895d..95bb58b0 100644 --- a/.github/ci/benchmark_config.json +++ b/.github/ci/benchmark_config.json @@ -107,12 +107,16 @@ }, { "address": "0x02000000", - "paths": ["yolo/weights_region.bin"], + "paths": [ + "yolo/weights_region.bin" + ], "required": true }, { "address": "0x04A00000", - "paths": ["yolo/coco_room_000139_raw_480x640x3_uint8_rgb.bin"], + "paths": [ + "yolo/coco_room_000139_raw_480x640x3_uint8_rgb.bin" + ], "required": true } ], @@ -122,7 +126,11 @@ "image_count": 5, "min_image_count": 5, "reference_contract": ".github/ci/reference/yolo.json", - "source_shape": [480, 640, 3] + "source_shape": [ + 480, + 640, + 3 + ] }, "benchmark_cases": [ { @@ -130,7 +138,9 @@ "file_loads": [ { "address": "0x04A00000", - "paths": ["yolo/coco_room_000139_raw_480x640x3_uint8_rgb.bin"], + "paths": [ + "yolo/coco_room_000139_raw_480x640x3_uint8_rgb.bin" + ], "required": true } ], @@ -146,7 +156,9 @@ "file_loads": [ { "address": "0x04A00000", - "paths": ["yolo/coco_cat_524280_raw_480x640x3_uint8_rgb.bin"], + "paths": [ + "yolo/coco_cat_524280_raw_480x640x3_uint8_rgb.bin" + ], "required": true } ], @@ -162,7 +174,9 @@ "file_loads": [ { "address": "0x04A00000", - "paths": ["yolo/coco_giraffes_296969_raw_480x640x3_uint8_rgb.bin"], + "paths": [ + "yolo/coco_giraffes_296969_raw_480x640x3_uint8_rgb.bin" + ], "required": true } ], @@ -178,7 +192,9 @@ "file_loads": [ { "address": "0x04A00000", - "paths": ["yolo/coco_elephants_445248_raw_480x640x3_uint8_rgb.bin"], + "paths": [ + "yolo/coco_elephants_445248_raw_480x640x3_uint8_rgb.bin" + ], "required": true } ], @@ -194,7 +210,9 @@ "file_loads": [ { "address": "0x04A00000", - "paths": ["yolo/coco_baseball_043816_raw_480x640x3_uint8_rgb.bin"], + "paths": [ + "yolo/coco_baseball_043816_raw_480x640x3_uint8_rgb.bin" + ], "required": true } ], @@ -234,17 +252,24 @@ "file_loads": [ { "address": "0x0", - "paths": ["zero2m.bin", "common/zero2m.bin"], + "paths": [ + "zero2m.bin", + "common/zero2m.bin" + ], "required": true }, { "address": "0x2000", - "paths": ["dncnn/dncnn20l64_input.bin"], + "paths": [ + "dncnn/dncnn20l64_input.bin" + ], "required": true }, { "address": "0x14000", - "paths": ["dncnn/dncnn20l64_weights.bin"], + "paths": [ + "dncnn/dncnn20l64_weights.bin" + ], "required": true } ], @@ -253,7 +278,10 @@ "accuracy": { "kind": "uint8_npy", "offset": "0x10000", - "shape": [64, 64], + "shape": [ + 64, + 64 + ], "max_abs": 2, "reference_path": "ported_models/dncnn/refs/dncnn20l64_reference.npy", "comment": "Gates the 64x64 denoised output @0x10000 against the PyTorch/deepinv oracle (refs/dncnn20l64_reference.npy, produced by scripts/gen_dncnn_oracle.py running deepinv.models.DnCNN on the pinned weights). Board-verified: the int8 kernel matches the FP32 oracle at max_abs=1 (3/3 board runs); gate max_abs<=2 is a 1-unit margin." @@ -315,6 +343,12 @@ }, "smolvlm_500m": { "config": "ported_models/llama_cpp_et/benchmarks/smolvlm_500m.json" + }, + "mamba_1_4b": { + "config": "ported_models/llama_cpp_et/benchmarks/mamba_1_4b.json" + }, + "chatglm3_6b": { + "config": "ported_models/llama_cpp_et/benchmarks/chatglm3_6b.json" } } } diff --git a/ported_models/chatglm3_6b/docs/RECIPE.md b/ported_models/chatglm3_6b/docs/RECIPE.md new file mode 100644 index 00000000..2a996d87 --- /dev/null +++ b/ported_models/chatglm3_6b/docs/RECIPE.md @@ -0,0 +1,55 @@ +# ChatGLM3-6B Porting Recipe + +## Overview + +Adds `zai-org/chatglm3-6b` (6B-parameter causal LM, Zhipu AI's ChatGLM3; +this model was previously published under `THUDM/chatglm3-6b`, which now +redirects to `zai-org`) to the `llama.cpp-et` framework. Confirmed via +local GGUF metadata inspection: `general.architecture = chatglm` -- +distinct from `glm4` (already ported earlier in this campaign), a +separate, older execution family in llama.cpp (ChatGLM uses a distinct +attention-bias/RoPE convention from GLM4). + +## Model Reference + +- **Source**: `zai-org/chatglm3-6b` (Hugging Face), revision + `e9e0406d062cdb887444fe5bd546833920abd4ac` +- **License**: Apache-2.0 +- **GGUF source**: `hellork/chatglm3-6b-128k-Q8_0-GGUF` (a 128k-context + fine-tune/extension of the base model, same architecture), file + `chatglm3-6b-128k-q8_0.gguf` +- **Quantization**: Q8_0, + `sha256=805e3761a997486eb08f45e0f74efa5c1cc0be8475afa2b170263b490a3ba8c8` + (verified locally against the downloaded file) +- **Architecture**: `arch = chatglm` per GGUF metadata, 199 tensors. + +## Verification performed this round + +Host reference: built a plain CPU-only (`GGML_ET=OFF`) configuration of the +same vendored `llama.cpp-et` source and ran `llama-perplexity` against the +board-pinned WikiText-2 corpus (`wikitext2_raw_test`, +`sha256=173c87a53759e0201f33e0ccf978e510c2042d7f2cb78229d9a50d79b9e7dd08`), +context 128 / batch 128 / ubatch 128 / 4 chunks. The model loads and runs +cleanly: + +``` +Final estimate: PPL = 15.9100 +/- 3.37450 +``` + +## Why this port likely needs no new ET-SoC1 kernel work + +`LLM_ARCH_CHATGLM`'s graph builder uses standard ops already proven on the +ET backend (RMSNorm, RoPE, MHA/GQA with a QKV bias term, GELU-based FFN) -- +no new op type. ET-SoC1 board execution itself is not something this +session can produce. + +## Open items for maintainer review + +- Registered in `artifacts.json`, `ported_models/llama_cpp_et/benchmarks/chatglm3_6b.json`, + and `.github/ci/benchmark_config.json` (port 18140) -- board-testable now, + independent of the model-ports track claim below. +- `ported_models/submissions/model_ports/chatglm3_6b.json` is the + model-ports track claim, pending identity approval. +- No changes to any protected file or the vendored submodule. +- GGUF used is a 128k-context fine-tune, not a base-model quant -- same + architecture and weights lineage, flagged for transparency. diff --git a/ported_models/chatglm3_6b/oracle/perplexity_oracle.json b/ported_models/chatglm3_6b/oracle/perplexity_oracle.json new file mode 100644 index 00000000..5a0e193a --- /dev/null +++ b/ported_models/chatglm3_6b/oracle/perplexity_oracle.json @@ -0,0 +1,25 @@ +{ + "oracle_type": "perplexity_threshold", + "model_artifact": { + "repo": "hellork/chatglm3-6b-128k-Q8_0-GGUF", + "revision": "main", + "filename": "chatglm3-6b-128k-q8_0.gguf", + "sha256": "805e3761a997486eb08f45e0f74efa5c1cc0be8475afa2b170263b490a3ba8c8" + }, + "corpus": { + "artifact": "wikitext2_raw_test", + "sha256": "173c87a53759e0201f33e0ccf978e510c2042d7f2cb78229d9a50d79b9e7dd08" + }, + "command": "llama-perplexity --model chatglm3-6b-128k-Q8_0.gguf -f wiki.test.raw -c 128 -b 128 -ub 128 --chunks 4", + "reference_run": { + "final_ppl": 15.91, + "final_ppl_stderr": 3.3745, + "measured_on": "CPU (ggml-cpu backend, GGML_ET=OFF build)", + "measured_date": "2026-07-25" + }, + "comparison_threshold": { + "metric": "final_ppl", + "max_relative_deviation": 0.2, + "note": "Matches this repo's own leaderboard-gate policy (PPL must stay within 20% of best-seen value). A full-offload ET-SoC1 re-run against this exact command/corpus/artifact should land at final_ppl within [12.73, 19.09] to be considered consistent with this reference run. No ET-SoC1 hardware was available to this session to perform that re-run directly." + } +} diff --git a/ported_models/flan_t5_base/docs/RECIPE.md b/ported_models/flan_t5_base/docs/RECIPE.md new file mode 100644 index 00000000..496d0637 --- /dev/null +++ b/ported_models/flan_t5_base/docs/RECIPE.md @@ -0,0 +1,67 @@ +# FLAN-T5-base -- Inconclusive Result (No Claim Filed) + +## Summary + +Attempted to add `google/flan-t5-base` (250M-parameter encoder-decoder +causal LM, an instruction-tuned T5) to the `llama.cpp-et` framework. +**The model loads and its compute graph builds successfully, but neither of +the two standard tools in this vendored `llama.cpp-et` submodule +(`llama-perplexity`, `llama-cli`) can actually drive it to produce output.** +No model-ports claim is filed -- this recipe documents the finding rather +than a working port. + +## Model Reference + +- **Source**: `google/flan-t5-base` (Hugging Face), revision + `7bcac572ce56db69c1ea7c8af255c5d7c9672fc2` +- **License**: Apache-2.0 +- **GGUF source**: `Felladrin/gguf-flan-t5-base`, file + `flan-t5-base.Q8_0.gguf` +- **Quantization**: Q8_0, + `sha256=73eb18e2341b28f40e9596c3740ef46941075a57c79af1ebffab177fd66cbe50` + (verified locally against the downloaded file) +- **Architecture**: `arch = t5` per GGUF metadata, 282 tensors. + +## What actually happens (both confirmed live, not speculative) + +The model loads cleanly and reserves a compute graph (`llama_kv_cache` +allocated, 704 graph nodes) -- so far identical to every working port in +this campaign. Then: + +1. **`llama-perplexity`** crashes with + `GGML_ASSERT(!llama_vocab_get_add_eos(vocab)) failed`. T5's tokenizer + always appends an EOS token (a fixed property of its seq2seq + vocabulary) -- the perplexity tool's raw-continuation PPL method + explicitly asserts the OPPOSITE for every model it evaluates, since + that method assumes a plain causal-LM tokenizer. This is a tool/model + mismatch, not a model defect. +2. **`llama-cli`** crashes with + `GGML_ASSERT(!cross->seq_ids_enc.empty() && "llama_encode must be called + first") failed`. T5 is encoder-decoder: its cross-attention layers need + the encoder pass (`llama_encode()`) run once before any decoder step + (`llama_decode()`). `llama-cli` goes straight to `llama_decode()` -- + it never calls `llama_encode()` at all. The underlying library + (`libllama`) clearly supports the encode/decode split (the assert + exists specifically to catch exactly this ordering mistake), but + neither CLI frontend in this vendored build orchestrates it. + +## Why no claim is filed + +Both failures happen in the harness/tooling, not the model itself -- the +GGUF is valid and the graph builds. But this campaign's standard is +"prove the model actually runs and produces output," and neither available +tool can demonstrate that for an encoder-decoder model. Filing a claim on +"it loads" alone, with the same evidence bar as this campaign's actually- +completed ports, would overstate what was actually shown. This is a +different category from `bitnet_2b` (which fails at model load) -- +here the model format is fine, but this repo's tooling has no +encoder-decoder driver. + +## What would need to change + +A custom driver that calls `llama_encode()` once against the input, then +loops `llama_decode()` for the output tokens (this is exactly what +llama.cpp's upstream examples do for T5/text2text tasks in some example +programs, but that driver is not present in the ported subset of tools +built in this repo's vendored submodule). Out of scope for a model-port +recipe -- would be new tooling work, not board wiring. diff --git a/ported_models/llama_cpp_et/artifacts.json b/ported_models/llama_cpp_et/artifacts.json index 9c419ae1..7ca704c5 100644 --- a/ported_models/llama_cpp_et/artifacts.json +++ b/ported_models/llama_cpp_et/artifacts.json @@ -485,6 +485,40 @@ "sha256": "d1eb8b6b23979205fdf63703ed10f788131a3f812c7b1f72e0119d5d81295150", "size_bytes": 108783360, "note": "SmolVLM 500M vision projector (SigLIP ~93M + MLP). Q8_0 quantized. Must be loaded alongside smolvlm_500m_q8_gguf." + }, + "mamba_1_4b_q6k_gguf": { + "kind": "model", + "framework": "llama.cpp-et", + "variant": "mamba-1.4b-hf-Q6_K", + "filename": "mamba-1.4b-hf-Q6_K.gguf", + "env": "MAMBA_1_4B_MODEL_PATH", + "source": { + "type": "huggingface", + "repo": "RichardErkhov/state-spaces_-_mamba-1.4b-hf-gguf", + "revision": "main", + "filename": "mamba-1.4b-hf.Q6_K.gguf", + "url": "https://huggingface.co/RichardErkhov/state-spaces_-_mamba-1.4b-hf-gguf/resolve/main/mamba-1.4b-hf.Q6_K.gguf" + }, + "sha256": "a5dde81ce41c34213bf26bcaf2ba26cd1c6fde20fd20b5af6a4a76a5272478bc", + "local_cache": "local-artifacts/models/mamba-1.4b-hf-Q6_K.gguf", + "board_path": "/data/models/mamba-1.4b-hf-Q6_K.gguf" + }, + "chatglm3_6b_q8_gguf": { + "kind": "model", + "framework": "llama.cpp-et", + "variant": "chatglm3-6b-128k-Q8_0", + "filename": "chatglm3-6b-128k-Q8_0.gguf", + "env": "CHATGLM3_6B_MODEL_PATH", + "source": { + "type": "huggingface", + "repo": "hellork/chatglm3-6b-128k-Q8_0-GGUF", + "revision": "main", + "filename": "chatglm3-6b-128k-q8_0.gguf", + "url": "https://huggingface.co/hellork/chatglm3-6b-128k-Q8_0-GGUF/resolve/main/chatglm3-6b-128k-q8_0.gguf" + }, + "sha256": "805e3761a997486eb08f45e0f74efa5c1cc0be8475afa2b170263b490a3ba8c8", + "local_cache": "local-artifacts/models/chatglm3-6b-128k-Q8_0.gguf", + "board_path": "/data/models/chatglm3-6b-128k-Q8_0.gguf" } } } diff --git a/ported_models/llama_cpp_et/benchmarks/chatglm3_6b.json b/ported_models/llama_cpp_et/benchmarks/chatglm3_6b.json new file mode 100644 index 00000000..5c356198 --- /dev/null +++ b/ported_models/llama_cpp_et/benchmarks/chatglm3_6b.json @@ -0,0 +1,52 @@ +{ + "runner": "llama_server", + "board": true, + "framework": { + "name": "llama.cpp-et", + "runner": "llama_server", + "source_artifact": "llama_cpp_source" + }, + "artifacts_file": "../artifacts.json", + "canonical_variant": "chatglm3-6b-128k-Q8_0", + "score": { + "metric": "tokens_per_second", + "label": "Decode tokens/s", + "higher_is_better": true + }, + "llama_server": { + "source_artifact": "llama_cpp_source", + "model_artifact": "chatglm3_6b_q8_gguf", + "server_artifact": "llama_server", + "workdir_artifact": "llama_cpp_build", + "host": "127.0.0.1", + "port": 18140, + "device": "ET", + "gpu_layers": 99, + "ctx_size": 2048, + "batch_size": 256, + "ubatch_size": 128, + "parallel": 1, + "cache_ram_mib": 0, + "ready_timeout_s": 300, + "request_timeout_s": 420, + "flash_attn": false, + "api": "completion", + "prompt": "Repeat this token sequence without commentary: OK OK OK OK OK OK OK OK OK OK", + "max_tokens": 96, + "temperature": 0, + "ignore_eos": true, + "min_completion_tokens": 32, + "perplexity": { + "enabled": true, + "perplexity_artifact": "llama_perplexity", + "corpus_artifact": "wikitext2_raw_test", + "ctx_size": 128, + "batch_size": 128, + "ubatch_size": 128, + "timeout_s": 420, + "min_ppl": 1.0, + "max_ppl": 1000.0, + "chunks": 4 + } + } +} diff --git a/ported_models/llama_cpp_et/benchmarks/mamba_1_4b.json b/ported_models/llama_cpp_et/benchmarks/mamba_1_4b.json new file mode 100644 index 00000000..d02cdc16 --- /dev/null +++ b/ported_models/llama_cpp_et/benchmarks/mamba_1_4b.json @@ -0,0 +1,52 @@ +{ + "runner": "llama_server", + "board": true, + "framework": { + "name": "llama.cpp-et", + "runner": "llama_server", + "source_artifact": "llama_cpp_source" + }, + "artifacts_file": "../artifacts.json", + "canonical_variant": "mamba-1.4b-hf-Q6_K", + "score": { + "metric": "tokens_per_second", + "label": "Decode tokens/s", + "higher_is_better": true + }, + "llama_server": { + "source_artifact": "llama_cpp_source", + "model_artifact": "mamba_1_4b_q6k_gguf", + "server_artifact": "llama_server", + "workdir_artifact": "llama_cpp_build", + "host": "127.0.0.1", + "port": 18139, + "device": "ET", + "gpu_layers": 99, + "ctx_size": 2048, + "batch_size": 256, + "ubatch_size": 128, + "parallel": 1, + "cache_ram_mib": 0, + "ready_timeout_s": 300, + "request_timeout_s": 420, + "flash_attn": false, + "api": "completion", + "prompt": "Repeat this token sequence without commentary: OK OK OK OK OK OK OK OK OK OK", + "max_tokens": 96, + "temperature": 0, + "ignore_eos": true, + "min_completion_tokens": 32, + "perplexity": { + "enabled": true, + "perplexity_artifact": "llama_perplexity", + "corpus_artifact": "wikitext2_raw_test", + "ctx_size": 128, + "batch_size": 128, + "ubatch_size": 128, + "timeout_s": 420, + "min_ppl": 1.0, + "max_ppl": 1000.0, + "chunks": 4 + } + } +} diff --git a/ported_models/mamba_1_4b/docs/RECIPE.md b/ported_models/mamba_1_4b/docs/RECIPE.md new file mode 100644 index 00000000..4e4dd7ea --- /dev/null +++ b/ported_models/mamba_1_4b/docs/RECIPE.md @@ -0,0 +1,66 @@ +# Mamba-1.4B Porting Recipe + +## Overview + +Adds `state-spaces/mamba-1.4b-hf` (1.4B-parameter State Space Model, not a +transformer) to the `llama.cpp-et` framework. Confirmed via local GGUF +metadata inspection: `general.architecture = mamba` -- a completely +different compute paradigm from every other model in this campaign +(no attention, no KV cache; a recurrent SSM state updated per token via +selective scan). + +## Model Reference + +- **Source**: `state-spaces/mamba-1.4b-hf` (Hugging Face), revision + `6e46eae61c27280517feef46f536d16b91076f08`. HF repo metadata has no + `license` tag and the README does not state one -- flagging honestly + rather than assuming Apache-2.0 just because the reference Mamba GitHub + repo uses that license. +- **GGUF source**: `RichardErkhov/state-spaces_-_mamba-1.4b-hf-gguf`, file + `mamba-1.4b-hf.Q6_K.gguf` (no Q8_0 available at this source -- highest + quant offered is Q6_K) +- **Quantization**: Q6_K, + `sha256=a5dde81ce41c34213bf26bcaf2ba26cd1c6fde20fd20b5af6a4a76a5272478bc` + (verified locally against the downloaded file) +- **Architecture**: `arch = mamba` per GGUF metadata, 482 tensors. + +## Verification performed this round + +Host reference: built a plain CPU-only (`GGML_ET=OFF`) configuration of the +same vendored `llama.cpp-et` source and ran `llama-perplexity` against the +board-pinned WikiText-2 corpus (`wikitext2_raw_test`, +`sha256=173c87a53759e0201f33e0ccf978e510c2042d7f2cb78229d9a50d79b9e7dd08`), +context 128 / batch 128 / ubatch 128 / 4 chunks. The model loads and runs +cleanly, using a **recurrent memory cache** instead of the usual +transformer KV cache (`llama_memory_recurrent`, 1 cell instead of 256 -- +SSM state is a fixed-size running summary, not a growing per-token cache): + +``` +Final estimate: PPL = 11.7985 +/- 1.97189 +``` + +This confirms `GGML_OP_SSM_CONV`/`GGML_OP_SSM_SCAN` (the ops Mamba's +selective-scan recurrence needs) work correctly on the CPU backend -- the +first genuinely non-attention architecture exercised in this campaign. + +## Why this port's ET-SoC1 kernel support is a real, open question + +CPU-backend success does not prove the ET-SoC1 backend supports +`SSM_CONV`/`SSM_SCAN` at all. Unlike the MoE routing question for +granitemoe (where `MUL_MAT_ID` was at least listed in `ggml-et.cpp`'s +op-coverage audit from earlier in this campaign), these SSM-specific ops +were not checked against `ggml-et.cpp` this round. Flagging as completely +open, not a formality -- this may be a genuine ET-SoC1 blocker similar to +this campaign's RWKV-6/PLaMo-2 findings (both blocked on a different +missing op, `GGML_OP_CPY`). + +## Open items for maintainer review + +- Registered in `artifacts.json`, `ported_models/llama_cpp_et/benchmarks/mamba_1_4b.json`, + and `.github/ci/benchmark_config.json` (port 18139) -- board-testable now + (this will directly answer the SSM-op-support question above), + independent of the model-ports track claim below. +- `ported_models/submissions/model_ports/mamba_1_4b.json` is the + model-ports track claim, pending identity approval. +- No changes to any protected file or the vendored submodule. +- License unspecified in the HF repo metadata -- do not assume Apache-2.0. diff --git a/ported_models/mamba_1_4b/oracle/perplexity_oracle.json b/ported_models/mamba_1_4b/oracle/perplexity_oracle.json new file mode 100644 index 00000000..53a29abb --- /dev/null +++ b/ported_models/mamba_1_4b/oracle/perplexity_oracle.json @@ -0,0 +1,25 @@ +{ + "oracle_type": "perplexity_threshold", + "model_artifact": { + "repo": "RichardErkhov/state-spaces_-_mamba-1.4b-hf-gguf", + "revision": "main", + "filename": "mamba-1.4b-hf.Q6_K.gguf", + "sha256": "a5dde81ce41c34213bf26bcaf2ba26cd1c6fde20fd20b5af6a4a76a5272478bc" + }, + "corpus": { + "artifact": "wikitext2_raw_test", + "sha256": "173c87a53759e0201f33e0ccf978e510c2042d7f2cb78229d9a50d79b9e7dd08" + }, + "command": "llama-perplexity --model mamba-1.4b-hf-Q6_K.gguf -f wiki.test.raw -c 128 -b 128 -ub 128 --chunks 4", + "reference_run": { + "final_ppl": 11.7985, + "final_ppl_stderr": 1.97189, + "measured_on": "CPU (ggml-cpu backend, GGML_ET=OFF build)", + "measured_date": "2026-07-25" + }, + "comparison_threshold": { + "metric": "final_ppl", + "max_relative_deviation": 0.2, + "note": "Matches this repo's own leaderboard-gate policy (PPL must stay within 20% of best-seen value). A full-offload ET-SoC1 re-run against this exact command/corpus/artifact should land at final_ppl within [9.44, 14.16] to be considered consistent with this reference run. No ET-SoC1 hardware was available to this session to perform that re-run directly." + } +} diff --git a/ported_models/submissions/model_ports/chatglm3_6b.json b/ported_models/submissions/model_ports/chatglm3_6b.json new file mode 100644 index 00000000..82db663f --- /dev/null +++ b/ported_models/submissions/model_ports/chatglm3_6b.json @@ -0,0 +1,16 @@ +{ + "schema_version": 1, + "track": "most_models_ported", + "benchmark_model": "chatglm3_6b", + "identity_id": "chatglm", + "source": { + "repo": "zai-org/chatglm3-6b", + "revision": "e9e0406d062cdb887444fe5bd546833920abd4ac", + "license": "apache-2.0" + }, + "implementation_paths": [ + "ported_models/chatglm3_6b" + ], + "benchmark_config": "ported_models/llama_cpp_et/benchmarks/chatglm3_6b.json", + "recipe": "ported_models/chatglm3_6b/docs/RECIPE.md" +} diff --git a/ported_models/submissions/model_ports/mamba_1_4b.json b/ported_models/submissions/model_ports/mamba_1_4b.json new file mode 100644 index 00000000..ab4acca2 --- /dev/null +++ b/ported_models/submissions/model_ports/mamba_1_4b.json @@ -0,0 +1,16 @@ +{ + "schema_version": 1, + "track": "most_models_ported", + "benchmark_model": "mamba_1_4b", + "identity_id": "mamba", + "source": { + "repo": "state-spaces/mamba-1.4b-hf", + "revision": "6e46eae61c27280517feef46f536d16b91076f08", + "license": "unspecified" + }, + "implementation_paths": [ + "ported_models/mamba_1_4b" + ], + "benchmark_config": "ported_models/llama_cpp_et/benchmarks/mamba_1_4b.json", + "recipe": "ported_models/mamba_1_4b/docs/RECIPE.md" +}