This is a gpt-4o-distil-Llama-3.3-70B-Instruct fine-tune, produced through P-E-W's Heretic (v1.2.0) abliteration engine with Magnitude-Preserving Orthogonal Ablation enabled.

Edit: This model is weird. Unable to refuse in standard prose, it writes python scripts with print statements or variables that refuse the request in non-standard ways. I have seen similar fallback safety mechanisms in various other models in the form of disclaimers or overt non-compliance, but writing code to refuse is wild. Still, it's pretty decensored. I cannot test it as much as I would like to due to lack of locally installed hardware capacity. Feedback is welcome.

Heretication Results

Score Metric	Value	Parameter	Value
Refusals	9/104	direction_index	per layer
KL Divergence	0.0347	attn.o_proj.max_weight	1.93
Initial Refusals	102/104	attn.o_proj.max_weight_position	17.32
		attn.o_proj.min_weight	1.92
		attn.o_proj.min_weight_distance	43.65
		mlp.down_proj.max_weight	0.64
		mlp.down_proj.max_weight_position	19.49
		mlp.down_proj.min_weight	0.07
		mlp.down_proj.min_weight_distance	78.30

Appendix

Empty system prompt.

 » [Trial  75] Refusals:  9/104, KL divergence: 0.0347
   [Trial 104] Refusals: 10/104, KL divergence: 0.0315
   [Trial 150] Refusals: 13/104, KL divergence: 0.0276
   [Trial 167] Refusals: 15/104, KL divergence: 0.0251
   [Trial 109] Refusals: 20/104, KL divergence: 0.0232
   [Trial 112] Refusals: 21/104, KL divergence: 0.0209
   [Trial  97] Refusals: 25/104, KL divergence: 0.0196
   [Trial 168] Refusals: 28/104, KL divergence: 0.0186
   [Trial  87] Refusals: 30/104, KL divergence: 0.0178
   [Trial  37] Refusals: 33/104, KL divergence: 0.0166
   [Trial 153] Refusals: 36/104, KL divergence: 0.0161
   [Trial  99] Refusals: 37/104, KL divergence: 0.0157
   [Trial 189] Refusals: 38/104, KL divergence: 0.0157
   [Trial 174] Refusals: 40/104, KL divergence: 0.0146
   [Trial 196] Refusals: 41/104, KL divergence: 0.0145
   [Trial  79] Refusals: 42/104, KL divergence: 0.0140
   [Trial 128] Refusals: 43/104, KL divergence: 0.0137
   [Trial 195] Refusals: 45/104, KL divergence: 0.0129
   [Trial 172] Refusals: 49/104, KL divergence: 0.0119
   [Trial 136] Refusals: 53/104, KL divergence: 0.0105
   [Trial  25] Refusals: 54/104, KL divergence: 0.0097
   [Trial 181] Refusals: 57/104, KL divergence: 0.0095
   [Trial  54] Refusals: 62/104, KL divergence: 0.0082
   [Trial 187] Refusals: 66/104, KL divergence: 0.0072
   [Trial  35] Refusals: 70/104, KL divergence: 0.0055
   [Trial  53] Refusals: 79/104, KL divergence: 0.0055
   [Trial  13] Refusals: 81/104, KL divergence: 0.0049
   [Trial  90] Refusals: 85/104, KL divergence: 0.0042
   [Trial  21] Refusals: 88/104, KL divergence: 0.0037
   [Trial  62] Refusals: 91/104, KL divergence: 0.0036
   [Trial 148] Refusals: 92/104, KL divergence: 0.0031
   [Trial   1] Refusals: 93/104, KL divergence: 0.0025
   [Trial 119] Refusals: 94/104, KL divergence: 0.0025
   [Trial 165] Refusals: 95/104, KL divergence: 0.0023
   [Trial 156] Refusals: 96/104, KL divergence: 0.0023
   [Trial  82] Refusals: 97/104, KL divergence: 0.0018
   [Trial  48] Refusals: 98/104, KL divergence: 0.0014
   [Trial  55] Refusals: 99/104, KL divergence: 0.0013
   [Trial  22] Refusals: 100/104, KL divergence: 0.0013
   [Trial   9] Refusals: 101/104, KL divergence: 0.0012
   [Trial 117] Refusals: 102/104, KL divergence: 0.0011

Residual Geometry

┏━━━━━━━┳━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━━┳━━━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┳━━━━━━━━┓
┃ Layer ┃ S(g,b) ┃ S(g*,b*) ┃  S(g,r) ┃ S(g*,r*) ┃  S(b,r) ┃ S(b*,r*) ┃    |g| ┃   |g*| ┃    |b| ┃   |b*| ┃    |r| ┃   |r*| ┃   Silh ┃
┡━━━━━━━╇━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━━╇━━━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━╇━━━━━━━━┩
│     1 │ 0.9956 │   0.9952 │ -0.0868 │  -0.0962 │  0.0070 │   0.0018 │   0.45 │   0.45 │   0.45 │   0.45 │   0.04 │   0.04 │ 0.1804 │
│     2 │ 0.9945 │   0.9941 │ -0.0484 │  -0.0548 │  0.0561 │   0.0540 │   0.52 │   0.52 │   0.52 │   0.52 │   0.05 │   0.06 │ 0.1761 │
│     3 │ 0.9888 │   0.9878 │ -0.1691 │  -0.1849 │ -0.0198 │  -0.0299 │   0.61 │   0.61 │   0.60 │   0.60 │   0.09 │   0.09 │ 0.1972 │
│     4 │ 0.9894 │   0.9889 │ -0.2148 │  -0.2280 │ -0.0708 │  -0.0808 │   0.85 │   0.86 │   0.84 │   0.84 │   0.12 │   0.13 │ 0.1600 │
│     5 │ 0.9836 │   0.9828 │ -0.2254 │  -0.2383 │ -0.0458 │  -0.0547 │   0.95 │   0.96 │   0.93 │   0.93 │   0.17 │   0.18 │ 0.1708 │
│     6 │ 0.9768 │   0.9757 │ -0.2380 │  -0.2522 │ -0.0246 │  -0.0342 │   1.09 │   1.09 │   1.06 │   1.06 │   0.23 │   0.24 │ 0.1796 │
│     7 │ 0.9750 │   0.9741 │ -0.2535 │  -0.2687 │ -0.0324 │  -0.0438 │   1.24 │   1.25 │   1.20 │   1.20 │   0.28 │   0.28 │ 0.1774 │
│     8 │ 0.9674 │   0.9668 │ -0.2454 │  -0.2598 │  0.0082 │  -0.0042 │   1.54 │   1.55 │   1.50 │   1.50 │   0.39 │   0.40 │ 0.1783 │
│     9 │ 0.9649 │   0.9646 │ -0.2716 │  -0.2810 │ -0.0091 │  -0.0181 │   1.83 │   1.84 │   1.76 │   1.76 │   0.48 │   0.48 │ 0.1712 │
│    10 │ 0.9397 │   0.9395 │ -0.2178 │  -0.2246 │  0.1292 │   0.1228 │   1.90 │   1.91 │   1.87 │   1.87 │   0.66 │   0.66 │ 0.1671 │
│    11 │ 0.9346 │   0.9345 │ -0.1906 │  -0.1956 │  0.1710 │   0.1662 │   2.08 │   2.08 │   2.07 │   2.07 │   0.75 │   0.75 │ 0.1538 │
│    12 │ 0.9291 │   0.9290 │ -0.2163 │  -0.2151 │  0.1600 │   0.1616 │   2.54 │   2.54 │   2.51 │   2.51 │   0.95 │   0.95 │ 0.1456 │
│    13 │ 0.9315 │   0.9315 │ -0.1908 │  -0.1938 │  0.1792 │   0.1764 │   2.84 │   2.85 │   2.83 │   2.84 │   1.05 │   1.05 │ 0.1514 │
│    14 │ 0.9039 │   0.9038 │ -0.1919 │  -0.1945 │  0.2465 │   0.2441 │   3.06 │   3.07 │   3.10 │   3.10 │   1.35 │   1.35 │ 0.1714 │
│    15 │ 0.8760 │   0.8762 │ -0.1617 │  -0.1648 │  0.3344 │   0.3310 │   3.38 │   3.40 │   3.54 │   3.55 │   1.73 │   1.73 │ 0.1990 │
│    16 │ 0.8565 │   0.8572 │ -0.2078 │  -0.2087 │  0.3268 │   0.3248 │   3.75 │   3.76 │   3.88 │   3.88 │   2.05 │   2.05 │ 0.2183 │
│    17 │ 0.8419 │   0.8415 │ -0.2487 │  -0.2492 │  0.3133 │   0.3135 │   3.96 │   3.97 │   4.04 │   4.05 │   2.25 │   2.26 │ 0.2316 │
│    18 │ 0.8634 │   0.8628 │ -0.3343 │  -0.3404 │  0.1868 │   0.1817 │   4.97 │   4.99 │   4.76 │   4.78 │   2.55 │   2.57 │ 0.2290 │
│    19 │ 0.8244 │   0.8230 │ -0.2838 │  -0.2885 │  0.3088 │   0.3065 │   5.12 │   5.14 │   5.17 │   5.18 │   3.05 │   3.07 │ 0.2362 │
│    20 │ 0.7963 │   0.7931 │ -0.2662 │  -0.2732 │  0.3712 │   0.3692 │   4.99 │   5.02 │   5.18 │   5.20 │   3.25 │   3.29 │ 0.2442 │
│    21 │ 0.8157 │   0.8132 │ -0.2597 │  -0.2673 │  0.3468 │   0.3435 │   5.58 │   5.61 │   5.75 │   5.76 │   3.44 │   3.48 │ 0.2579 │
│    22 │ 0.7708 │   0.7684 │ -0.2226 │  -0.2269 │  0.4495 │   0.4490 │   5.25 │   5.28 │   5.73 │   5.75 │   3.75 │   3.78 │ 0.2665 │
│    23 │ 0.7653 │   0.7625 │ -0.2071 │  -0.2101 │  0.4712 │   0.4723 │   5.04 │   5.06 │   5.59 │   5.61 │   3.68 │   3.71 │ 0.2653 │
│    24 │ 0.7129 │   0.7084 │ -0.2047 │  -0.2051 │  0.5405 │   0.5455 │   5.21 │   5.22 │   6.06 │   6.10 │   4.34 │   4.40 │ 0.2743 │
│    25 │ 0.6840 │   0.6789 │ -0.2283 │  -0.2310 │  0.5541 │   0.5575 │   5.14 │   5.17 │   6.01 │   6.05 │   4.51 │   4.57 │ 0.2760 │
│    26 │ 0.6983 │   0.6936 │ -0.2291 │  -0.2335 │  0.5368 │   0.5385 │   5.33 │   5.38 │   6.15 │   6.21 │   4.53 │   4.60 │ 0.2658 │
│    27 │ 0.6600 │   0.6554 │ -0.2151 │  -0.2203 │  0.5917 │   0.5923 │   5.70 │   5.76 │   6.91 │   6.98 │   5.31 │   5.40 │ 0.2832 │
│    28 │ 0.6256 │   0.6202 │ -0.2287 │  -0.2341 │  0.6164 │   0.6174 │   5.73 │   5.79 │   7.09 │   7.16 │   5.68 │   5.78 │ 0.2949 │
│    29 │ 0.6010 │   0.5933 │ -0.2367 │  -0.2435 │  0.6343 │   0.6363 │   5.67 │   5.73 │   7.12 │   7.21 │   5.86 │   5.98 │ 0.3012 │    
│    30 │ 0.6007 │   0.5929 │ -0.2400 │  -0.2461 │  0.6319 │   0.6346 │   5.77 │   5.83 │   7.22 │   7.32 │   5.95 │   6.08 │ 0.3010 │
│    31 │ 0.5913 │   0.5834 │ -0.2388 │  -0.2468 │  0.6419 │   0.6431 │   5.79 │   5.87 │   7.34 │   7.43 │   6.09 │   6.23 │ 0.3093 │
│    32 │ 0.5965 │   0.5880 │ -0.2360 │  -0.2451 │  0.6391 │   0.6400 │   6.07 │   6.16 │   7.67 │   7.77 │   6.33 │   6.48 │ 0.3104 │
│    33 │ 0.5763 │   0.5661 │ -0.2582 │  -0.2700 │  0.6407 │   0.6409 │   6.42 │   6.52 │   8.08 │   8.18 │   6.83 │   7.01 │ 0.3210 │
│    34 │ 0.5836 │   0.5731 │ -0.2253 │  -0.2382 │  0.6597 │   0.6594 │   6.69 │   6.80 │   8.67 │   8.79 │   7.23 │   7.41 │ 0.3249 │
│    35 │ 0.5922 │   0.5812 │ -0.2490 │  -0.2622 │  0.6330 │   0.6329 │   6.70 │   6.80 │   8.38 │   8.48 │   6.98 │   7.15 │ 0.3216 │
│    36 │ 0.5817 │   0.5718 │ -0.2454 │  -0.2573 │  0.6458 │   0.6456 │   6.69 │   6.78 │   8.49 │   8.58 │   7.13 │   7.29 │ 0.3126 │
│    37 │ 0.5846 │   0.5738 │ -0.2334 │  -0.2473 │  0.6524 │   0.6517 │   6.80 │   6.89 │   8.72 │   8.81 │   7.28 │   7.44 │ 0.3053 │
│    38 │ 0.5685 │   0.5594 │ -0.2415 │  -0.2524 │  0.6610 │   0.6609 │   7.13 │   7.21 │   9.22 │   9.30 │   7.82 │   7.96 │ 0.2977 │
│    39 │ 0.5636 │   0.5545 │ -0.2466 │  -0.2568 │  0.6615 │   0.6619 │   7.25 │   7.33 │   9.37 │   9.45 │   7.98 │   8.14 │ 0.2960 │
│    40 │ 0.5695 │   0.5601 │ -0.2585 │  -0.2692 │  0.6469 │   0.6470 │   7.63 │   7.72 │   9.66 │   9.75 │   8.22 │   8.38 │ 0.2882 │
│    41 │ 0.5672 │   0.5577 │ -0.2659 │  -0.2764 │  0.6432 │   0.6436 │   7.78 │   7.88 │   9.80 │   9.89 │   8.37 │   8.54 │ 0.2831 │
│    42 │ 0.5502 │   0.5409 │ -0.2422 │  -0.2517 │  0.6769 │   0.6779 │   7.95 │   8.05 │  10.48 │  10.59 │   9.02 │   9.21 │ 0.2859 │
│    43 │ 0.5482 │   0.5385 │ -0.2500 │  -0.2597 │  0.6727 │   0.6739 │   8.17 │   8.27 │  10.69 │  10.81 │   9.24 │   9.43 │ 0.2808 │
│    44 │ 0.5465 │   0.5369 │ -0.2424 │  -0.2521 │  0.6800 │   0.6810 │   8.34 │   8.44 │  11.04 │  11.16 │   9.53 │   9.73 │ 0.2757 │
│    45 │ 0.5464 │   0.5369 │ -0.2533 │  -0.2624 │  0.6718 │   0.6732 │   8.77 │   8.87 │  11.46 │  11.58 │   9.92 │  10.12 │ 0.2726 │
│    46 │ 0.5373 │   0.5280 │ -0.2464 │  -0.2544 │  0.6850 │   0.6870 │   8.89 │   8.99 │  11.83 │  11.96 │  10.29 │  10.50 │ 0.2713 │
│    47 │ 0.5270 │   0.5174 │ -0.2336 │  -0.2420 │  0.7032 │   0.7051 │   8.95 │   9.05 │  12.24 │  12.38 │  10.70 │  10.92 │ 0.2702 │
│    48 │ 0.5299 │   0.5201 │ -0.2219 │  -0.2300 │  0.7093 │   0.7116 │   9.25 │   9.34 │  12.79 │  12.94 │  11.12 │  11.36 │ 0.2670 │
│    49 │ 0.5258 │   0.5161 │ -0.2184 │  -0.2260 │  0.7153 │   0.7178 │   9.54 │   9.64 │  13.33 │  13.49 │  11.62 │  11.86 │ 0.2648 │
│    50 │ 0.5274 │   0.5176 │ -0.2106 │  -0.2179 │  0.7195 │   0.7223 │   9.91 │  10.00 │  13.94 │  14.12 │  12.12 │  12.38 │ 0.2643 │
│    51 │ 0.5325 │   0.5227 │ -0.2051 │  -0.2124 │  0.7192 │   0.7221 │  10.17 │  10.26 │  14.32 │  14.50 │  12.38 │  12.65 │ 0.2585 │
│    52 │ 0.5319 │   0.5218 │ -0.2064 │  -0.2133 │  0.7188 │   0.7221 │  10.53 │  10.63 │  14.82 │  15.01 │  12.83 │  13.11 │ 0.2566 │
│    53 │ 0.5346 │   0.5245 │ -0.2121 │  -0.2190 │  0.7125 │   0.7159 │  11.03 │  11.13 │  15.37 │  15.55 │  13.29 │  13.57 │ 0.2527 │
│    54 │ 0.5351 │   0.5248 │ -0.2101 │  -0.2172 │  0.7135 │   0.7169 │  11.34 │  11.45 │  15.83 │  16.03 │  13.68 │  13.98 │ 0.2499 │
│    55 │ 0.5342 │   0.5242 │ -0.2051 │  -0.2122 │  0.7178 │   0.7210 │  11.56 │  11.67 │  16.26 │  16.46 │  14.04 │  14.34 │ 0.2455 │
│    56 │ 0.5426 │   0.5326 │ -0.1891 │  -0.1963 │  0.7223 │   0.7254 │  11.92 │  12.03 │  16.92 │  17.13 │  14.48 │  14.79 │ 0.2429 │
│    57 │ 0.5448 │   0.5351 │ -0.1848 │  -0.1924 │  0.7235 │   0.7261 │  12.37 │  12.48 │  17.61 │  17.81 │  15.03 │  15.33 │ 0.2367 │
│    58 │ 0.5455 │   0.5360 │ -0.1822 │  -0.1895 │  0.7247 │   0.7274 │  12.63 │  12.75 │  18.03 │  18.24 │  15.37 │  15.68 │ 0.2317 │
│    59 │ 0.5449 │   0.5352 │ -0.1750 │  -0.1825 │  0.7302 │   0.7329 │  12.86 │  12.97 │  18.53 │  18.75 │  15.78 │  16.10 │ 0.2299 │
│    60 │ 0.5415 │   0.5318 │ -0.1675 │  -0.1748 │  0.7381 │   0.7408 │  13.08 │  13.20 │  19.12 │  19.35 │  16.30 │  16.64 │ 0.2296 │
│    61 │ 0.5460 │   0.5363 │ -0.1628 │  -0.1703 │  0.7377 │   0.7404 │  13.53 │  13.65 │  19.77 │  20.01 │  16.79 │  17.14 │ 0.2273 │
│    62 │ 0.5450 │   0.5357 │ -0.1571 │  -0.1642 │  0.7424 │   0.7450 │  13.85 │  13.97 │  20.41 │  20.65 │  17.33 │  17.68 │ 0.2251 │
│    63 │ 0.5465 │   0.5373 │ -0.1477 │  -0.1550 │  0.7475 │   0.7499 │  14.06 │  14.19 │  20.94 │  21.19 │  17.73 │  18.09 │ 0.2240 │
│    64 │ 0.5478 │   0.5384 │ -0.1454 │  -0.1526 │  0.7481 │   0.7506 │  14.46 │  14.58 │  21.55 │  21.81 │  18.23 │  18.60 │ 0.2233 │
│    65 │ 0.5496 │   0.5403 │ -0.1418 │  -0.1485 │  0.7491 │   0.7519 │  14.74 │  14.86 │  22.03 │  22.29 │  18.59 │  18.96 │ 0.2189 │
│    66 │ 0.5515 │   0.5425 │ -0.1358 │  -0.1423 │  0.7515 │   0.7544 │  14.99 │  15.10 │  22.51 │  22.77 │  18.95 │  19.33 │ 0.2166 │
│    67 │ 0.5554 │   0.5464 │ -0.1373 │  -0.1435 │  0.7474 │   0.7505 │  15.51 │  15.63 │  23.13 │  23.40 │  19.42 │  19.80 │ 0.2161 │
│    68 │ 0.5617 │   0.5526 │ -0.1339 │  -0.1404 │  0.7447 │   0.7476 │  16.04 │  16.16 │  23.82 │  24.10 │  19.89 │  20.28 │ 0.2147 │
│    69 │ 0.5639 │   0.5548 │ -0.1355 │  -0.1417 │  0.7418 │   0.7450 │  16.50 │  16.62 │  24.38 │  24.66 │  20.32 │  20.72 │ 0.2121 │
│    70 │ 0.5743 │   0.5655 │ -0.1462 │  -0.1513 │  0.7259 │   0.7297 │  17.47 │  17.58 │  25.13 │  25.41 │  20.79 │  21.20 │ 0.2111 │
│    71 │ 0.5846 │   0.5760 │ -0.1398 │  -0.1449 │  0.7216 │   0.7254 │  18.06 │  18.18 │  25.84 │  26.13 │  21.17 │  21.58 │ 0.2093 │
│    72 │ 0.5948 │   0.5865 │ -0.1361 │  -0.1411 │  0.7155 │   0.7191 │  18.75 │  18.87 │  26.59 │  26.88 │  21.58 │  21.99 │ 0.2060 │
│    73 │ 0.5964 │   0.5883 │ -0.1241 │  -0.1294 │  0.7224 │   0.7257 │  19.39 │  19.51 │  27.83 │  28.12 │  22.51 │  22.93 │ 0.2062 │
│    74 │ 0.6186 │   0.6110 │ -0.1062 │  -0.1108 │  0.7156 │   0.7191 │  20.84 │  20.95 │  29.66 │  29.96 │  23.44 │  23.87 │ 0.2041 │
│    75 │ 0.6324 │   0.6252 │ -0.0907 │  -0.0952 │  0.7141 │   0.7174 │  22.56 │  22.68 │  32.10 │  32.40 │  24.97 │  25.40 │ 0.2064 │
│    76 │ 0.6282 │   0.6214 │ -0.0907 │  -0.0947 │  0.7179 │   0.7211 │  23.79 │  23.90 │  34.03 │  34.34 │  26.59 │  27.03 │ 0.2008 │
│    77 │ 0.6257 │   0.6189 │ -0.0792 │  -0.0832 │  0.7280 │   0.7312 │  25.52 │  25.62 │  37.11 │  37.43 │  29.04 │  29.50 │ 0.2046 │
│    78 │ 0.6483 │   0.6419 │ -0.0529 │  -0.0569 │  0.7260 │   0.7290 │  27.72 │  27.82 │  40.25 │  40.57 │  30.69 │  31.16 │ 0.2007 │
│    79 │ 0.6718 │   0.6660 │ -0.0079 │  -0.0100 │  0.7354 │   0.7392 │  32.04 │  32.07 │  47.28 │  47.62 │  35.02 │  35.53 │ 0.1996 │
│    80 │ 0.7264 │   0.7224 │ -0.0470 │  -0.0586 │  0.6524 │   0.6480 │ 112.18 │ 113.71 │ 147.85 │ 149.04 │ 101.72 │ 103.24 │ 0.1946 │
└───────┴────────┴──────────┴─────────┴──────────┴─────────┴──────────┴────────┴────────┴────────┴────────┴────────┴────────┴────────┘
g = mean of residual vectors for good prompts
g* = geometric median of residual vectors for good prompts
b = mean of residual vectors for bad prompts
b* = geometric median of residual vectors for bad prompts
r = refusal direction for means (i.e., b - g)
r* = refusal direction for geometric medians (i.e., b* - g*)
S(x,y) = cosine similarity of x and y
|x| = L2 norm of x
Silh = Mean silhouette coefficient of residuals for good/bad clusters

Model Card for llama-3.3-70b-4o-final

This model is a fine-tuned version of meta-llama/Llama-3.3-70B-Instruct. It has been trained using TRL.

Quick start

python

from transformers import pipeline

question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
generator = pipeline("text-generation", model="None", device="cuda")
output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
print(output["generated_text"])

Training procedure

Visualize in Weights & Biases

This model was trained with SFT.

Framework versions

PEFT 0.18.1
TRL: 0.27.1
Transformers: 5.0.0
Pytorch: 2.9.0.dev20250708+cu128
Datasets: 4.5.0
Tokenizers: 0.22.2

Citations

Cite TRL as:

bibtex

@misc{vonwerra2022trl,
	title        = {{TRL: Transformer Reinforcement Learning}},
	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
	year         = 2020,
	journal      = {GitHub repository},
	publisher    = {GitHub},
	howpublished = {\url{https://github.com/huggingface/trl}}
}

MuXodious/gpt-4o-distil-Llama-3.3-70B-Instruct-PaperWitch-heresy

Model Card for llama-3.3-70b-4o-final

Quick start

Training procedure

Framework versions

Citations

MuXodious/
gpt-4o-distil-Llama-3.3-70B-Instruct-PaperWitch-heresy