tarekziade HF Staff
Publish MIC usage, slim fixture and reviewed Transformers expectations
732c0b9 verified | { | |
| "mic": "0.3", | |
| "name": "RecurrentGemma causal LM", | |
| "usage": "AutoTokenizer + AutoModelForCausalLM, batched causal LM with left padding, inference logits and one SGD step", | |
| "architecture": "RecurrentGemmaForCausalLM", | |
| "checkpoints": { | |
| "google/recurrentgemma-2b": { | |
| "fixture": "huggingface-mic/recurrentgemma-2b-mic" | |
| } | |
| }, | |
| "fixtures": { | |
| "huggingface-mic/recurrentgemma-2b-mic": { | |
| "built_from": "google/recurrentgemma-2b", | |
| "covers": [ | |
| "google/recurrentgemma-2b" | |
| ], | |
| "build": { | |
| "seed": 17, | |
| "config_overrides": { | |
| "fields": { | |
| "num_hidden_layers": 3 | |
| }, | |
| "reason": "The generic rule shrinks to 2 layers, and block_types (recurrent, recurrent, attention) makes both of them recurrent: the fixture would have no attention block, so attention_mask is never read and padding goes untested. A third layer adds one sliding-window attention block, as in the checkpoint's repeating pattern." | |
| } | |
| } | |
| } | |
| }, | |
| "integrations": { | |
| "transformers": { | |
| "entry_point": "integrations/transformers/usage.md", | |
| "format": "runnable-markdown", | |
| "requires": [ | |
| "transformers>=5", | |
| "torch" | |
| ], | |
| "targets": [ | |
| "fixtures", | |
| "checkpoints" | |
| ], | |
| "variants": { | |
| "default": {}, | |
| "eager": { | |
| "attn_implementation": "eager" | |
| }, | |
| "bfloat16": { | |
| "dtype": "bfloat16" | |
| } | |
| }, | |
| "training": true, | |
| "resources": { | |
| "fixture": { | |
| "memory_gb": 4, | |
| "download_mb": 40 | |
| }, | |
| "google/recurrentgemma-2b": { | |
| "devices": [ | |
| "cuda" | |
| ], | |
| "gpu_memory_gb": 18, | |
| "memory_gb": 16, | |
| "download_mb": 10750, | |
| "variants": { | |
| "bfloat16": { | |
| "gpu_memory_gb": 10 | |
| } | |
| } | |
| } | |
| } | |
| } | |
| }, | |
| "outputs": { | |
| "runtime": { | |
| "compare": "exact" | |
| }, | |
| "logits.last": { | |
| "compare": "allclose", | |
| "atol": 0.0001, | |
| "rtol": 0.0001 | |
| }, | |
| "logits.first_real": { | |
| "compare": "allclose", | |
| "atol": 0.0001, | |
| "rtol": 0.0001 | |
| }, | |
| "training.loss": { | |
| "compare": "allclose", | |
| "atol": 0.0001, | |
| "rtol": 0.0001 | |
| }, | |
| "training.gradients": { | |
| "compare": "all_true" | |
| }, | |
| "training.updated": { | |
| "compare": "true" | |
| } | |
| } | |
| } | |