Instructions to use enseven/lfm-2.5-think-code with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use enseven/lfm-2.5-think-code with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("LiquidAI/LFM2.5-1.2B-Thinking") model = PeftModel.from_pretrained(base_model, "enseven/lfm-2.5-think-code") - Notebooks
- Google Colab
- Kaggle
Download pilot-report.json from enseven/lfm-2.5-think-code: direct link, hf CLI and curl.
- Browser
- Download file 5.72 kB
-
https://huggingface.co/enseven/lfm-2.5-think-code/resolve/main/pilot-report.json
- Command line
-
hf download hf://enseven/lfm-2.5-think-code/pilot-report.json
-
curl -L -o pilot-report.json https://huggingface.co/enseven/lfm-2.5-think-code/resolve/main/pilot-report.json
5.72 kB
| { | |
| "schema_version": 1, | |
| "report": "e3-pilot", | |
| "generated_at_utc": "2026-09-12", | |
| "suite_id": "e3-humanevalplus-pilot-v1", | |
| "rows": { | |
| "original-bf16": { | |
| "generation_evidence": "reports/e3/e3-pilot-20260912T131807Z", | |
| "generation_summary": { | |
| "task_count": 33, | |
| "generation_record_count": 33, | |
| "terminal_record_count": 33, | |
| "retried_task_count": 0, | |
| "infrastructure_failure_count": 0, | |
| "duplicate_generation_keys": 0, | |
| "total_completion_tokens": 52186, | |
| "generated_programs_executed": 0 | |
| }, | |
| "extraction_yield": 0.848485, | |
| "failed_extraction_task_ids": [ | |
| "HumanEval/148", | |
| "HumanEval/163", | |
| "HumanEval/32", | |
| "HumanEval/52", | |
| "HumanEval/57" | |
| ], | |
| "scoring_evidence": "reports/e3/e3-pilot-20260912T131807Z/original-bf16/scoring/e3-score-20260912T133052406Z", | |
| "pass_at_1_base": 0.75, | |
| "pass_at_1_plus": 0.7142857142857143, | |
| "scores_computed": 28, | |
| "mean_decode_tokens_per_second": 112.3 | |
| }, | |
| "merged-bf16": { | |
| "generation_evidence": "reports/e3/e3-pilot-20260912T131705Z", | |
| "generation_summary": { | |
| "task_count": 33, | |
| "generation_record_count": 33, | |
| "terminal_record_count": 33, | |
| "retried_task_count": 0, | |
| "infrastructure_failure_count": 0, | |
| "duplicate_generation_keys": 0, | |
| "total_completion_tokens": 3578, | |
| "generated_programs_executed": 0 | |
| }, | |
| "extraction_yield": 1.0, | |
| "failed_extraction_task_ids": [], | |
| "scoring_evidence": "reports/e3/e3-pilot-20260912T131705Z/merged-bf16/scoring/e3-score-20260912T133017638Z", | |
| "pass_at_1_base": 0.36363636363636365, | |
| "pass_at_1_plus": 0.2727272727272727, | |
| "scores_computed": 33, | |
| "mean_decode_tokens_per_second": 122.1 | |
| }, | |
| "q8_0": { | |
| "generation_evidence": "reports/e3/e3-pilot-20260912T132635Z", | |
| "generation_summary": { | |
| "task_count": 33, | |
| "generation_record_count": 33, | |
| "terminal_record_count": 33, | |
| "retried_task_count": 0, | |
| "infrastructure_failure_count": 0, | |
| "duplicate_generation_keys": 0, | |
| "total_completion_tokens": 3582, | |
| "generated_programs_executed": 0 | |
| }, | |
| "extraction_yield": 1.0, | |
| "failed_extraction_task_ids": [], | |
| "scoring_evidence": "reports/e3/e3-pilot-20260912T132635Z/q8_0/scoring/e3-score-20260912T133124723Z", | |
| "pass_at_1_base": 0.36363636363636365, | |
| "pass_at_1_plus": 0.2727272727272727, | |
| "scores_computed": 33, | |
| "mean_decode_tokens_per_second": 197.2 | |
| }, | |
| "q6_k": { | |
| "generation_evidence": "reports/e3/e3-pilot-20260912T132714Z", | |
| "generation_summary": { | |
| "task_count": 33, | |
| "generation_record_count": 33, | |
| "terminal_record_count": 33, | |
| "retried_task_count": 0, | |
| "infrastructure_failure_count": 0, | |
| "duplicate_generation_keys": 0, | |
| "total_completion_tokens": 3541, | |
| "generated_programs_executed": 0 | |
| }, | |
| "extraction_yield": 1.0, | |
| "failed_extraction_task_ids": [], | |
| "scoring_evidence": "reports/e3/e3-pilot-20260912T132714Z/q6_k/scoring/e3-score-20260912T133148491Z", | |
| "pass_at_1_base": 0.36363636363636365, | |
| "pass_at_1_plus": 0.30303030303030304, | |
| "scores_computed": 33, | |
| "mean_decode_tokens_per_second": 201.8 | |
| } | |
| }, | |
| "paired_deltas": { | |
| "fine_tune_effect_plus_original_to_merged": { | |
| "gained": [], | |
| "lost": [ | |
| "HumanEval/1", | |
| "HumanEval/102", | |
| "HumanEval/107", | |
| "HumanEval/128", | |
| "HumanEval/133", | |
| "HumanEval/138", | |
| "HumanEval/158", | |
| "HumanEval/37", | |
| "HumanEval/62", | |
| "HumanEval/72", | |
| "HumanEval/87", | |
| "HumanEval/92" | |
| ] | |
| }, | |
| "quant_effect_plus_merged_to_q8_0": { | |
| "lost": [] | |
| }, | |
| "quant_effect_plus_merged_to_q6_k": { | |
| "lost": [] | |
| } | |
| }, | |
| "findings": { | |
| "harness_health": { | |
| "infrastructure_failures": 0, | |
| "retried_tasks": 0, | |
| "duplicate_keys": 0, | |
| "rows_completed": 4, | |
| "generated_programs_executed_host": 0 | |
| }, | |
| "fine_tune_effect": "Negative on this pilot slice: original plus 0.714 (28 scored, yield 0.848 -> at most 0.606 if all unextractable scored zero) vs merged plus 0.273 (33 scored). Twelve paired losses, zero gains.", | |
| "quantization_effect": "Essentially lossless at pilot scale: Q8_0 identical to merged; Q6_K no paired losses and one plus gain.", | |
| "caveats": [ | |
| "n=33 tasks, one greedy sample per task; exact deltas carry slice noise until the sealed 128-task run.", | |
| "Original-row extraction yield 0.848 reflects reasoning-leakage outputs of the base thinking model under prompt v1; absence scores zero, which slightly favors the fine-tune in the paired delta and cannot explain it.", | |
| "KodCode contamination caveat applies to absolute scores; the paired delta remains the scientific comparison." | |
| ] | |
| }, | |
| "frozen_e4_decisions": { | |
| "sealed_model_rows": [ | |
| "original-bf16", | |
| "merged-bf16", | |
| "q8_0", | |
| "q6_k" | |
| ], | |
| "deployment_quant": "q6_k (no paired loss vs merged BF16, one plus gain, 963 MB vs 1246 MB)", | |
| "deployment_quant_gate": "Q6_K deployable iff sealed pass@1(plus) within 2 pp of merged-bf16 AND no paired loss pattern absent from merged; frozen before any sealed request.", | |
| "harness_health_gates": "Infra failure rate <= 2% of requests; extraction yield reported per row as model evidence, not a harness pass gate (original-row 0.848 is a model property)." | |
| } | |
| } | |