Repository: unslothai/unsloth

Issue #476: [URGENT] llama.cpp / GGUF breaks on Colab
Created: 2024-05-16T13:38:25Z
llama.cpp seems to be unable to install - investigating now.

Duplicate issue #413: Quantization (q4_k_m gguf) failed for Phi-3
Created: 2024-05-02T16:47:23Z
When run Alpaca + Phi-3 3.8b full example.ipynb in https://colab.research.google.com/drive/1NvkBmkHfucGO3Ve9s1NKZvMNlw5p83ym?usp=sharing, in last step to save quantization model:
# Save to q4_k_m GGUF
if True: model.save_pretrained_gguf("model", tokenizer, quantization_method = "q4_k_m")

the error will occur:
Unsloth: Merging 4bit and LoRA weights to 16bit...
Unsloth: Will use up to 5.96 out of 12.67 RAM for saving.
100%|██████████| 32/32 [00:01<00:00, 19.69it/s]
Unsloth: Saving tokenizer... Done.
Unsloth: Saving model... This might take 5 minutes for Llama-7b...
Unsloth: Saving model/pytorch_model-00001-of-00002.bin...
Unsloth: Saving model/pytorch_model-00002-of-00002.bin...
Done.
==((====))==  Unsloth: Conversion from QLoRA to GGUF information
   \\   /|    [0] Installing llama.cpp will take 3 minutes.
O^O/ \_/ \    [1] Converting HF to GUUF 16bits will take 3 minutes.
\        /    [2] Converting GGUF 16bits to q4_k_m will take 20 minutes.
 "-____-"     In total, you will have to wait around 26 minutes.

Unsloth: [0] Installing llama.cpp. This will take 3 minutes...
Unsloth: [1] Converting model at model into f16 GGUF format.
The output location will be ./model-unsloth.F16.gguf
This will take 3 minutes...
Loading model file model/pytorch_model-00001-of-00002.bin
Loading model file model/pytorch_model-00001-of-00002.bin
Loading model file model/pytorch_model-00002-of-00002.bin
params = Params(n_vocab=32064, n_embd=3072, n_layer=32, n_ctx=4096, n_ff=8192, n_head=32, n_head_kv=32, n_experts=None, n_experts_used=None, f_norm_eps=1e-05, rope_scaling_type=None, f_rope_freq_base=10000.0, f_rope_scale=None, n_orig_ctx=None, rope_finetuned=None, ftype=<GGMLFileType.MostlyF16: 1>, path_model=PosixPath('model'))
Loaded vocab file PosixPath('model/tokenizer.model'), type 'spm'
Vocab info: <SentencePieceVocab with 32000 base tokens and 11 added tokens>
Special vocab info: <SpecialVocab with 0 merges, special tokens {'bos': 1, 'eos': 32000, 'unk': 0, 'pad': 32000}, add special tokens {'bos': True, 'eos': False}>
Permuting layer 0
Permuting layer 1
Permuting layer 2
Permuting layer 3
Permuting layer 4
Permuting layer 5
Permuting layer 6
Permuting layer 7
Permuting layer 8
Permuting layer 9
Permuting layer 10
Permuting layer 11
Permuting layer 12
Permuting layer 13
Permuting layer 14
Permuting layer 15
Permuting layer 16
Permuting layer 17
Permuting layer 18
Permuting layer 19
Permuting layer 20
Permuting layer 21
Permuting layer 22
Permuting layer 23
Permuting layer 24
Permuting layer 25
Permuting layer 26
Permuting layer 27
Permuting layer 28
Permuting layer 29
Permuting layer 30
Permuting layer 31
model.embed_tokens.weight                        -> token_embd.weight                        | F16    | [32064, 3072]
model.layers.0.self_attn.q_proj.weight           -> blk.0.attn_q.weight                      | F16    | [3072, 3072]
model.layers.0.self_attn.k_proj.weight           -> blk.0.attn_k.weight                      | F16    | [3072, 3072]
model.layers.0.self_attn.v_proj.weight           -> blk.0.attn_v.weight                      | F16    | [3072, 3072]
model.layers.0.self_attn.o_proj.weight           -> blk.0.attn_output.weight                 | F16    | [3072, 3072]
model.layers.0.mlp.gate_proj.weight              -> blk.0.ffn_gate.weight                    | F16    | [8192, 3072]
model.layers.0.mlp.up_proj.weight                -> blk.0.ffn_up.weight                      | F16    | [8192, 3072]
model.layers.0.mlp.down_proj.weight              -> blk.0.ffn_down.weight                    | F16    | [3072, 8192]
model.layers.0.input_layernorm.weight            -> blk.0.attn_norm.weight                   | F16    | [3072]
model.layers.0.post_attention_layernorm.weight   -> blk.0.ffn_norm.weight                    | F16    | [3072]
model.layers.1.self_attn.q_proj.weight           -> blk.1.attn_q.weight                      | F16    | [3072, 3072]
model.layers.1.self_attn.k_proj.weight           -> blk.1.attn_k.weight                      | F16    | [3072, 3072]
model.layers.1.self_attn.v_proj.weight           -> blk.1.attn_v.weight                      | F16    | [3072, 3072]
model.layers.1.self_attn.o_proj.weight           -> blk.1.attn_output.weight                 | F16    | [3072, 3072]
model.layers.1.mlp.gate_proj.weight              -> blk.1.ffn_gate.weight                    | F16    | [8192, 3072]
model.layers.1.mlp.up_proj.weight                -> blk.1.ffn_up.weight                      | F16    | [8192, 3072]
model.layers.1.mlp.down_proj.weight              -> blk.1.ffn_down.weight                    | F16    | [3072, 8192]
model.layers.1.input_layernorm.weight            -> blk.1.attn_norm.weight                   | F16    | [3072]
model.layers.1.post_attention_layernorm.weight   -> blk.1.ffn_norm.weight                    | F16    | [3072]
model.layers.2.self_attn.q_proj.weight           -> blk.2.attn_q.weight                      | F16    | [3072, 3072]
model.layers.2.self_attn.k_proj.weight           -> blk.2.attn_k.weight                      | F16    | [3072, 3072]
model.layers.2.self_attn.v_proj.weight           -> blk.2.attn_v.weight                      | F16    | [3072, 3072]
model.layers.2.self_attn.o_proj.weight           -> blk.2.attn_output.weight                 | F16    | [3072, 3072]
model.layers.2.mlp.gate_proj.weight              -> blk.2.ffn_gate.weight                    | F16    | [8192, 3072]
model.layers.2.mlp.up_proj.weight                -> blk.2.ffn_up.weight                      | F16    | [8192, 3072]
model.layers.2.mlp.down_proj.weight              -> blk.2.ffn_down.weight                    | F16    | [3072, 8192]
model.layers.2.input_layernorm.weight            -> blk.2.attn_norm.weight                   | F16    | [3072]
model.layers.2.post_attention_layernorm.weight   -> blk.2.ffn_norm.weight                    | F16    | [3072]
model.layers.3.self_attn.q_proj.weight           -> blk.3.attn_q.weight                      | F16    | [3072, 3072]
model.layers.3.self_attn.k_proj.weight           -> blk.3.attn_k.weight                      | F16    | [3072, 3072]
model.layers.3.self_attn.v_proj.weight           -> blk.3.attn_v.weight                      | F16    | [3072, 3072]
model.layers.3.self_attn.o_proj.weight           -> blk.3.attn_output.weight                 | F16    | [3072, 3072]
model.layers.3.mlp.gate_proj.weight              -> blk.3.ffn_gate.weight                    | F16    | [8192, 3072]
model.layers.3.mlp.up_proj.weight                -> blk.3.ffn_up.weight                      | F16    | [8192, 3072]
model.layers.3.mlp.down_proj.weight              -> blk.3.ffn_down.weight                    | F16    | [3072, 8192]
model.layers.3.input_layernorm.weight            -> blk.3.attn_norm.weight                   | F16    | [3072]
model.layers.3.post_attention_layernorm.weight   -> blk.3.ffn_norm.weight                    | F16    | [3072]
model.layers.4.self_attn.q_proj.weight           -> blk.4.attn_q.weight                      | F16    | [3072, 3072]
model.layers.4.self_attn.k_proj.weight           -> blk.4.attn_k.weight                      | F16    | [3072, 3072]
model.layers.4.self_attn.v_proj.weight           -> blk.4.attn_v.weight                      | F16    | [3072, 3072]
model.layers.4.self_attn.o_proj.weight           -> blk.4.attn_output.weight                 | F16    | [3072, 3072]
model.layers.4.mlp.gate_proj.weight              -> blk.4.ffn_gate.weight                    | F16    | [8192, 3072]
model.layers.4.mlp.up_proj.weight                -> blk.4.ffn_up.weight                      | F16    | [8192, 3072]
model.layers.4.mlp.down_proj.weight              -> blk.4.ffn_down.weight                    | F16    | [3072, 8192]
model.layers.4.input_layernorm.weight            -> blk.4.attn_norm.weight                   | F16    | [3072]
model.layers.4.post_attention_layernorm.weight   -> blk.4.ffn_norm.weight                    | F16    | [3072]
model.layers.5.self_attn.q_proj.weight           -> blk.5.attn_q.weight                      | F16    | [3072, 3072]
model.layers.5.self_attn.k_proj.weight           -> blk.5.attn_k.weight                      | F16    | [3072, 3072]
model.layers.5.self_attn.v_proj.weight           -> blk.5.attn_v.weight                      | F16    | [3072, 3072]
model.layers.5.self_attn.o_proj.weight           -> blk.5.attn_output.weight                 | F16    | [3072, 3072]
model.layers.5.mlp.gate_proj.weight              -> blk.5.ffn_gate.weight                    | F16    | [8192, 3072]
model.layers.5.mlp.up_proj.weight                -> blk.5.ffn_up.weight                      | F16    | [8192, 3072]
model.layers.5.mlp.down_proj.weight              -> blk.5.ffn_down.weight                    | F16    | [3072, 8192]
model.layers.5.input_layernorm.weight            -> blk.5.attn_norm.weight                   | F16    | [3072]
model.layers.5.post_attention_layernorm.weight   -> blk.5.ffn_norm.weight                    | F16    | [3072]
model.layers.6.self_attn.q_proj.weight           -> blk.6.attn_q.weight                      | F16    | [3072, 3072]
model.layers.6.self_attn.k_proj.weight           -> blk.6.attn_k.weight                      | F16    | [3072, 3072]
model.layers.6.self_attn.v_proj.weight           -> blk.6.attn_v.weight                      | F16    | [3072, 3072]
model.layers.6.self_attn.o_proj.weight           -> blk.6.attn_output.weight                 | F16    | [3072, 3072]
model.layers.6.mlp.gate_proj.weight              -> blk.6.ffn_gate.weight                    | F16    | [8192, 3072]
model.layers.6.mlp.up_proj.weight                -> blk.6.ffn_up.weight                      | F16    | [8192, 3072]
model.layers.6.mlp.down_proj.weight              -> blk.6.ffn_down.weight                    | F16    | [3072, 8192]
model.layers.6.input_layernorm.weight            -> blk.6.attn_norm.weight                   | F16    | [3072]
model.layers.6.post_attention_layernorm.weight   -> blk.6.ffn_norm.weight                    | F16    | [3072]
model.layers.7.self_attn.q_proj.weight           -> blk.7.attn_q.weight                      | F16    | [3072, 3072]
model.layers.7.self_attn.k_proj.weight           -> blk.7.attn_k.weight                      | F16    | [3072, 3072]
model.layers.7.self_attn.v_proj.weight           -> blk.7.attn_v.weight                      | F16    | [3072, 3072]
model.layers.7.self_attn.o_proj.weight           -> blk.7.attn_output.weight                 | F16    | [3072, 3072]
model.layers.7.mlp.gate_proj.weight              -> blk.7.ffn_gate.weight                    | F16    | [8192, 3072]
model.layers.7.mlp.up_proj.weight                -> blk.7.ffn_up.weight                      | F16    | [8192, 3072]
model.layers.7.mlp.down_proj.weight              -> blk.7.ffn_down.weight                    | F16    | [3072, 8192]
model.layers.7.input_layernorm.weight            -> blk.7.attn_norm.weight                   | F16    | [3072]
model.layers.7.post_attention_layernorm.weight   -> blk.7.ffn_norm.weight                    | F16    | [3072]
model.layers.8.self_attn.q_proj.weight           -> blk.8.attn_q.weight                      | F16    | [3072, 3072]
model.layers.8.self_attn.k_proj.weight           -> blk.8.attn_k.weight                      | F16    | [3072, 3072]
model.layers.8.self_attn.v_proj.weight           -> blk.8.attn_v.weight                      | F16    | [3072, 3072]
model.layers.8.self_attn.o_proj.weight           -> blk.8.attn_output.weight                 | F16    | [3072, 3072]
model.layers.8.mlp.gate_proj.weight              -> blk.8.ffn_gate.weight                    | F16    | [8192, 3072]
model.layers.8.mlp.up_proj.weight                -> blk.8.ffn_up.weight                      | F16    | [8192, 3072]
model.layers.8.mlp.down_proj.weight              -> blk.8.ffn_down.weight                    | F16    | [3072, 8192]
model.layers.8.input_layernorm.weight            -> blk.8.attn_norm.weight                   | F16    | [3072]
model.layers.8.post_attention_layernorm.weight   -> blk.8.ffn_norm.weight                    | F16    | [3072]
model.layers.9.self_attn.q_proj.weight           -> blk.9.attn_q.weight                      | F16    | [3072, 3072]
model.layers.9.self_attn.k_proj.weight           -> blk.9.attn_k.weight                      | F16    | [3072, 3072]
model.layers.9.self_attn.v_proj.weight           -> blk.9.attn_v.weight                      | F16    | [3072, 3072]
model.layers.9.self_attn.o_proj.weight           -> blk.9.attn_output.weight                 | F16    | [3072, 3072]
model.layers.9.mlp.gate_proj.weight              -> blk.9.ffn_gate.weight                    | F16    | [8192, 3072]
model.layers.9.mlp.up_proj.weight                -> blk.9.ffn_up.weight                      | F16    | [8192, 3072]
model.layers.9.mlp.down_proj.weight              -> blk.9.ffn_down.weight                    | F16    | [3072, 8192]
model.layers.9.input_layernorm.weight            -> blk.9.attn_norm.weight                   | F16    | [3072]
model.layers.9.post_attention_layernorm.weight   -> blk.9.ffn_norm.weight                    | F16    | [3072]
model.layers.10.self_attn.q_proj.weight          -> blk.10.attn_q.weight                     | F16    | [3072, 3072]
model.layers.10.self_attn.k_proj.weight          -> blk.10.attn_k.weight                     | F16    | [3072, 3072]
model.layers.10.self_attn.v_proj.weight          -> blk.10.attn_v.weight                     | F16    | [3072, 3072]
model.layers.10.self_attn.o_proj.weight          -> blk.10.attn_output.weight                | F16    | [3072, 3072]
model.layers.10.mlp.gate_proj.weight             -> blk.10.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.10.mlp.up_proj.weight               -> blk.10.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.10.mlp.down_proj.weight             -> blk.10.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.10.input_layernorm.weight           -> blk.10.attn_norm.weight                  | F16    | [3072]
model.layers.10.post_attention_layernorm.weight  -> blk.10.ffn_norm.weight                   | F16    | [3072]
model.layers.11.self_attn.q_proj.weight          -> blk.11.attn_q.weight                     | F16    | [3072, 3072]
model.layers.11.self_attn.k_proj.weight          -> blk.11.attn_k.weight                     | F16    | [3072, 3072]
model.layers.11.self_attn.v_proj.weight          -> blk.11.attn_v.weight                     | F16    | [3072, 3072]
model.layers.11.self_attn.o_proj.weight          -> blk.11.attn_output.weight                | F16    | [3072, 3072]
model.layers.11.mlp.gate_proj.weight             -> blk.11.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.11.mlp.up_proj.weight               -> blk.11.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.11.mlp.down_proj.weight             -> blk.11.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.11.input_layernorm.weight           -> blk.11.attn_norm.weight                  | F16    | [3072]
model.layers.11.post_attention_layernorm.weight  -> blk.11.ffn_norm.weight                   | F16    | [3072]
model.layers.12.self_attn.q_proj.weight          -> blk.12.attn_q.weight                     | F16    | [3072, 3072]
model.layers.12.self_attn.k_proj.weight          -> blk.12.attn_k.weight                     | F16    | [3072, 3072]
model.layers.12.self_attn.v_proj.weight          -> blk.12.attn_v.weight                     | F16    | [3072, 3072]
model.layers.12.self_attn.o_proj.weight          -> blk.12.attn_output.weight                | F16    | [3072, 3072]
model.layers.12.mlp.gate_proj.weight             -> blk.12.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.12.mlp.up_proj.weight               -> blk.12.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.12.mlp.down_proj.weight             -> blk.12.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.12.input_layernorm.weight           -> blk.12.attn_norm.weight                  | F16    | [3072]
model.layers.12.post_attention_layernorm.weight  -> blk.12.ffn_norm.weight                   | F16    | [3072]
model.layers.13.self_attn.q_proj.weight          -> blk.13.attn_q.weight                     | F16    | [3072, 3072]
model.layers.13.self_attn.k_proj.weight          -> blk.13.attn_k.weight                     | F16    | [3072, 3072]
model.layers.13.self_attn.v_proj.weight          -> blk.13.attn_v.weight                     | F16    | [3072, 3072]
model.layers.13.self_attn.o_proj.weight          -> blk.13.attn_output.weight                | F16    | [3072, 3072]
model.layers.13.mlp.gate_proj.weight             -> blk.13.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.13.mlp.up_proj.weight               -> blk.13.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.13.mlp.down_proj.weight             -> blk.13.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.13.input_layernorm.weight           -> blk.13.attn_norm.weight                  | F16    | [3072]
model.layers.13.post_attention_layernorm.weight  -> blk.13.ffn_norm.weight                   | F16    | [3072]
model.layers.14.self_attn.q_proj.weight          -> blk.14.attn_q.weight                     | F16    | [3072, 3072]
model.layers.14.self_attn.k_proj.weight          -> blk.14.attn_k.weight                     | F16    | [3072, 3072]
model.layers.14.self_attn.v_proj.weight          -> blk.14.attn_v.weight                     | F16    | [3072, 3072]
model.layers.14.self_attn.o_proj.weight          -> blk.14.attn_output.weight                | F16    | [3072, 3072]
model.layers.14.mlp.gate_proj.weight             -> blk.14.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.14.mlp.up_proj.weight               -> blk.14.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.14.mlp.down_proj.weight             -> blk.14.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.14.input_layernorm.weight           -> blk.14.attn_norm.weight                  | F16    | [3072]
model.layers.14.post_attention_layernorm.weight  -> blk.14.ffn_norm.weight                   | F16    | [3072]
model.layers.15.self_attn.q_proj.weight          -> blk.15.attn_q.weight                     | F16    | [3072, 3072]
model.layers.15.self_attn.k_proj.weight          -> blk.15.attn_k.weight                     | F16    | [3072, 3072]
model.layers.15.self_attn.v_proj.weight          -> blk.15.attn_v.weight                     | F16    | [3072, 3072]
model.layers.15.self_attn.o_proj.weight          -> blk.15.attn_output.weight                | F16    | [3072, 3072]
model.layers.15.mlp.gate_proj.weight             -> blk.15.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.15.mlp.up_proj.weight               -> blk.15.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.15.mlp.down_proj.weight             -> blk.15.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.15.input_layernorm.weight           -> blk.15.attn_norm.weight                  | F16    | [3072]
model.layers.15.post_attention_layernorm.weight  -> blk.15.ffn_norm.weight                   | F16    | [3072]
model.layers.16.self_attn.q_proj.weight          -> blk.16.attn_q.weight                     | F16    | [3072, 3072]
model.layers.16.self_attn.k_proj.weight          -> blk.16.attn_k.weight                     | F16    | [3072, 3072]
model.layers.16.self_attn.v_proj.weight          -> blk.16.attn_v.weight                     | F16    | [3072, 3072]
model.layers.16.self_attn.o_proj.weight          -> blk.16.attn_output.weight                | F16    | [3072, 3072]
model.layers.16.mlp.gate_proj.weight             -> blk.16.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.16.mlp.up_proj.weight               -> blk.16.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.16.mlp.down_proj.weight             -> blk.16.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.16.input_layernorm.weight           -> blk.16.attn_norm.weight                  | F16    | [3072]
model.layers.16.post_attention_layernorm.weight  -> blk.16.ffn_norm.weight                   | F16    | [3072]
model.layers.17.self_attn.q_proj.weight          -> blk.17.attn_q.weight                     | F16    | [3072, 3072]
model.layers.17.self_attn.k_proj.weight          -> blk.17.attn_k.weight                     | F16    | [3072, 3072]
model.layers.17.self_attn.v_proj.weight          -> blk.17.attn_v.weight                     | F16    | [3072, 3072]
model.layers.17.self_attn.o_proj.weight          -> blk.17.attn_output.weight                | F16    | [3072, 3072]
model.layers.17.mlp.gate_proj.weight             -> blk.17.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.17.mlp.up_proj.weight               -> blk.17.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.17.mlp.down_proj.weight             -> blk.17.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.17.input_layernorm.weight           -> blk.17.attn_norm.weight                  | F16    | [3072]
model.layers.17.post_attention_layernorm.weight  -> blk.17.ffn_norm.weight                   | F16    | [3072]
model.layers.18.self_attn.q_proj.weight          -> blk.18.attn_q.weight                     | F16    | [3072, 3072]
model.layers.18.self_attn.k_proj.weight          -> blk.18.attn_k.weight                     | F16    | [3072, 3072]
model.layers.18.self_attn.v_proj.weight          -> blk.18.attn_v.weight                     | F16    | [3072, 3072]
model.layers.18.self_attn.o_proj.weight          -> blk.18.attn_output.weight                | F16    | [3072, 3072]
model.layers.18.mlp.gate_proj.weight             -> blk.18.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.18.mlp.up_proj.weight               -> blk.18.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.18.mlp.down_proj.weight             -> blk.18.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.18.input_layernorm.weight           -> blk.18.attn_norm.weight                  | F16    | [3072]
model.layers.18.post_attention_layernorm.weight  -> blk.18.ffn_norm.weight                   | F16    | [3072]
model.layers.19.self_attn.q_proj.weight          -> blk.19.attn_q.weight                     | F16    | [3072, 3072]
model.layers.19.self_attn.k_proj.weight          -> blk.19.attn_k.weight                     | F16    | [3072, 3072]
model.layers.19.self_attn.v_proj.weight          -> blk.19.attn_v.weight                     | F16    | [3072, 3072]
model.layers.19.self_attn.o_proj.weight          -> blk.19.attn_output.weight                | F16    | [3072, 3072]
model.layers.19.mlp.gate_proj.weight             -> blk.19.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.19.mlp.up_proj.weight               -> blk.19.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.19.mlp.down_proj.weight             -> blk.19.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.19.input_layernorm.weight           -> blk.19.attn_norm.weight                  | F16    | [3072]
model.layers.19.post_attention_layernorm.weight  -> blk.19.ffn_norm.weight                   | F16    | [3072]
model.layers.20.self_attn.q_proj.weight          -> blk.20.attn_q.weight                     | F16    | [3072, 3072]
model.layers.20.self_attn.k_proj.weight          -> blk.20.attn_k.weight                     | F16    | [3072, 3072]
model.layers.20.self_attn.v_proj.weight          -> blk.20.attn_v.weight                     | F16    | [3072, 3072]
model.layers.20.self_attn.o_proj.weight          -> blk.20.attn_output.weight                | F16    | [3072, 3072]
model.layers.20.mlp.gate_proj.weight             -> blk.20.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.20.mlp.up_proj.weight               -> blk.20.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.20.mlp.down_proj.weight             -> blk.20.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.20.input_layernorm.weight           -> blk.20.attn_norm.weight                  | F16    | [3072]
model.layers.20.post_attention_layernorm.weight  -> blk.20.ffn_norm.weight                   | F16    | [3072]
model.layers.21.self_attn.q_proj.weight          -> blk.21.attn_q.weight                     | F16    | [3072, 3072]
model.layers.21.self_attn.k_proj.weight          -> blk.21.attn_k.weight                     | F16    | [3072, 3072]
model.layers.21.self_attn.v_proj.weight          -> blk.21.attn_v.weight                     | F16    | [3072, 3072]
model.layers.21.self_attn.o_proj.weight          -> blk.21.attn_output.weight                | F16    | [3072, 3072]
model.layers.21.mlp.gate_proj.weight             -> blk.21.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.21.mlp.up_proj.weight               -> blk.21.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.21.mlp.down_proj.weight             -> blk.21.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.21.input_layernorm.weight           -> blk.21.attn_norm.weight                  | F16    | [3072]
model.layers.21.post_attention_layernorm.weight  -> blk.21.ffn_norm.weight                   | F16    | [3072]
model.layers.22.self_attn.q_proj.weight          -> blk.22.attn_q.weight                     | F16    | [3072, 3072]
model.layers.22.self_attn.k_proj.weight          -> blk.22.attn_k.weight                     | F16    | [3072, 3072]
model.layers.22.self_attn.v_proj.weight          -> blk.22.attn_v.weight                     | F16    | [3072, 3072]
model.layers.22.self_attn.o_proj.weight          -> blk.22.attn_output.weight                | F16    | [3072, 3072]
model.layers.22.mlp.gate_proj.weight             -> blk.22.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.22.mlp.up_proj.weight               -> blk.22.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.22.mlp.down_proj.weight             -> blk.22.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.22.input_layernorm.weight           -> blk.22.attn_norm.weight                  | F16    | [3072]
model.layers.22.post_attention_layernorm.weight  -> blk.22.ffn_norm.weight                   | F16    | [3072]
model.layers.23.self_attn.q_proj.weight          -> blk.23.attn_q.weight                     | F16    | [3072, 3072]
model.layers.23.self_attn.k_proj.weight          -> blk.23.attn_k.weight                     | F16    | [3072, 3072]
model.layers.23.self_attn.v_proj.weight          -> blk.23.attn_v.weight                     | F16    | [3072, 3072]
model.layers.23.self_attn.o_proj.weight          -> blk.23.attn_output.weight                | F16    | [3072, 3072]
model.layers.23.mlp.gate_proj.weight             -> blk.23.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.23.mlp.up_proj.weight               -> blk.23.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.23.mlp.down_proj.weight             -> blk.23.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.23.input_layernorm.weight           -> blk.23.attn_norm.weight                  | F16    | [3072]
model.layers.23.post_attention_layernorm.weight  -> blk.23.ffn_norm.weight                   | F16    | [3072]
model.layers.24.self_attn.q_proj.weight          -> blk.24.attn_q.weight                     | F16    | [3072, 3072]
model.layers.24.self_attn.k_proj.weight          -> blk.24.attn_k.weight                     | F16    | [3072, 3072]
model.layers.24.self_attn.v_proj.weight          -> blk.24.attn_v.weight                     | F16    | [3072, 3072]
model.layers.24.self_attn.o_proj.weight          -> blk.24.attn_output.weight                | F16    | [3072, 3072]
model.layers.24.mlp.gate_proj.weight             -> blk.24.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.24.mlp.up_proj.weight               -> blk.24.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.24.mlp.down_proj.weight             -> blk.24.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.24.input_layernorm.weight           -> blk.24.attn_norm.weight                  | F16    | [3072]
model.layers.24.post_attention_layernorm.weight  -> blk.24.ffn_norm.weight                   | F16    | [3072]
model.layers.25.self_attn.q_proj.weight          -> blk.25.attn_q.weight                     | F16    | [3072, 3072]
model.layers.25.self_attn.k_proj.weight          -> blk.25.attn_k.weight                     | F16    | [3072, 3072]
model.layers.25.self_attn.v_proj.weight          -> blk.25.attn_v.weight                     | F16    | [3072, 3072]
model.layers.25.self_attn.o_proj.weight          -> blk.25.attn_output.weight                | F16    | [3072, 3072]
model.layers.25.mlp.gate_proj.weight             -> blk.25.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.25.mlp.up_proj.weight               -> blk.25.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.25.mlp.down_proj.weight             -> blk.25.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.25.input_layernorm.weight           -> blk.25.attn_norm.weight                  | F16    | [3072]
model.layers.25.post_attention_layernorm.weight  -> blk.25.ffn_norm.weight                   | F16    | [3072]
model.layers.26.self_attn.q_proj.weight          -> blk.26.attn_q.weight                     | F16    | [3072, 3072]
model.layers.26.self_attn.k_proj.weight          -> blk.26.attn_k.weight                     | F16    | [3072, 3072]
model.layers.26.self_attn.v_proj.weight          -> blk.26.attn_v.weight                     | F16    | [3072, 3072]
model.layers.26.self_attn.o_proj.weight          -> blk.26.attn_output.weight                | F16    | [3072, 3072]
model.layers.26.mlp.gate_proj.weight             -> blk.26.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.26.mlp.up_proj.weight               -> blk.26.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.26.mlp.down_proj.weight             -> blk.26.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.26.input_layernorm.weight           -> blk.26.attn_norm.weight                  | F16    | [3072]
model.layers.26.post_attention_layernorm.weight  -> blk.26.ffn_norm.weight                   | F16    | [3072]
model.layers.27.self_attn.q_proj.weight          -> blk.27.attn_q.weight                     | F16    | [3072, 3072]
model.layers.27.self_attn.k_proj.weight          -> blk.27.attn_k.weight                     | F16    | [3072, 3072]
model.layers.27.self_attn.v_proj.weight          -> blk.27.attn_v.weight                     | F16    | [3072, 3072]
model.layers.27.self_attn.o_proj.weight          -> blk.27.attn_output.weight                | F16    | [3072, 3072]
model.layers.27.mlp.gate_proj.weight             -> blk.27.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.27.mlp.up_proj.weight               -> blk.27.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.27.mlp.down_proj.weight             -> blk.27.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.27.input_layernorm.weight           -> blk.27.attn_norm.weight                  | F16    | [3072]
model.layers.27.post_attention_layernorm.weight  -> blk.27.ffn_norm.weight                   | F16    | [3072]
model.layers.28.self_attn.q_proj.weight          -> blk.28.attn_q.weight                     | F16    | [3072, 3072]
model.layers.28.self_attn.k_proj.weight          -> blk.28.attn_k.weight                     | F16    | [3072, 3072]
model.layers.28.self_attn.v_proj.weight          -> blk.28.attn_v.weight                     | F16    | [3072, 3072]
model.layers.28.self_attn.o_proj.weight          -> blk.28.attn_output.weight                | F16    | [3072, 3072]
model.layers.28.mlp.gate_proj.weight             -> blk.28.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.28.mlp.up_proj.weight               -> blk.28.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.28.mlp.down_proj.weight             -> blk.28.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.28.input_layernorm.weight           -> blk.28.attn_norm.weight                  | F16    | [3072]
model.layers.28.post_attention_layernorm.weight  -> blk.28.ffn_norm.weight                   | F16    | [3072]
model.layers.29.self_attn.q_proj.weight          -> blk.29.attn_q.weight                     | F16    | [3072, 3072]
model.layers.29.self_attn.k_proj.weight          -> blk.29.attn_k.weight                     | F16    | [3072, 3072]
model.layers.29.self_attn.v_proj.weight          -> blk.29.attn_v.weight                     | F16    | [3072, 3072]
model.layers.29.self_attn.o_proj.weight          -> blk.29.attn_output.weight                | F16    | [3072, 3072]
model.layers.29.mlp.gate_proj.weight             -> blk.29.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.29.mlp.up_proj.weight               -> blk.29.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.29.mlp.down_proj.weight             -> blk.29.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.29.input_layernorm.weight           -> blk.29.attn_norm.weight                  | F16    | [3072]
model.layers.29.post_attention_layernorm.weight  -> blk.29.ffn_norm.weight                   | F16    | [3072]
model.layers.30.self_attn.q_proj.weight          -> blk.30.attn_q.weight                     | F16    | [3072, 3072]
model.layers.30.self_attn.k_proj.weight          -> blk.30.attn_k.weight                     | F16    | [3072, 3072]
model.layers.30.self_attn.v_proj.weight          -> blk.30.attn_v.weight                     | F16    | [3072, 3072]
model.layers.30.self_attn.o_proj.weight          -> blk.30.attn_output.weight                | F16    | [3072, 3072]
model.layers.30.mlp.gate_proj.weight             -> blk.30.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.30.mlp.up_proj.weight               -> blk.30.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.30.mlp.down_proj.weight             -> blk.30.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.30.input_layernorm.weight           -> blk.30.attn_norm.weight                  | F16    | [3072]
model.layers.30.post_attention_layernorm.weight  -> blk.30.ffn_norm.weight                   | F16    | [3072]
model.layers.31.self_attn.q_proj.weight          -> blk.31.attn_q.weight                     | F16    | [3072, 3072]
model.layers.31.self_attn.k_proj.weight          -> blk.31.attn_k.weight                     | F16    | [3072, 3072]
model.layers.31.self_attn.v_proj.weight          -> blk.31.attn_v.weight                     | F16    | [3072, 3072]
model.layers.31.self_attn.o_proj.weight          -> blk.31.attn_output.weight                | F16    | [3072, 3072]
model.layers.31.mlp.gate_proj.weight             -> blk.31.ffn_gate.weight                   | F16    | [8192, 3072]
model.layers.31.mlp.up_proj.weight               -> blk.31.ffn_up.weight                     | F16    | [8192, 3072]
model.layers.31.mlp.down_proj.weight             -> blk.31.ffn_down.weight                   | F16    | [3072, 8192]
model.layers.31.input_layernorm.weight           -> blk.31.attn_norm.weight                  | F16    | [3072]
model.layers.31.post_attention_layernorm.weight  -> blk.31.ffn_norm.weight                   | F16    | [3072]
model.norm.weight                                -> output_norm.weight                       | F16    | [3072]
lm_head.weight                                   -> output.weight                            | F16    | [32064, 3072]
Writing model-unsloth.F16.gguf, format 1
---------------------------------------------------------------------------
RuntimeError                              Traceback (most recent call last)
[<ipython-input-16-2e4f2e9c1ca2>](https://localhost:8080/#) in <cell line: 10>()
      8 
      9 # Save to q4_k_m GGUF
---> 10 if True: model.save_pretrained_gguf("model", tokenizer, quantization_method = "q4_k_m")
     11 if False: model.push_to_hub_gguf("hf/model", tokenizer, quantization_method = "q4_k_m", token = "")

1 frames
[/usr/local/lib/python3.10/dist-packages/unsloth/save.py](https://localhost:8080/#) in save_to_gguf(model_type, model_directory, quantization_method, first_conversion, _run_installer)
    962             )
    963         else:
--> 964             raise RuntimeError(
    965                 f"Unsloth: Quantization failed for {final_location}\n"\
    966                 "You might have to compile llama.cpp yourself, then run this again.\n"\

RuntimeError: Unsloth: Quantization failed for ./model-unsloth.F16.gguf
You might have to compile llama.cpp yourself, then run this again.
You do not need to close this Python program. Run the following commands in a new terminal:
You must run this in the same folder as you're saving your model.
git clone --recursive https://github.com/ggerganov/llama.cpp
cd llama.cpp && make clean && LLAMA_CUDA=1 make all -j
Once that's done, redo the quantization.

Closing comment (2024-05-16T13:57:10Z): Probably related to #476