vbatts/llama.cpp
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convert-new.py : minor fixes

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Georgi Gerganov 2023-08-16 23:11:21 +03:00
parent c40ec5c403
commit f9db574bbf
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1 changed files with 8 additions and 8 deletions
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convert-new.py
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@ -142,7 +142,7 @@ class Params:
"Suggestion: provide 'config.json' of the model in the same directory containing model files.") "Suggestion: provide 'config.json' of the model in the same directory containing model files.")
n_head = n_embd // 128 # guessed n_head = n_embd // 128 # guessed
n_mult = 255 # guessed n_mult = 256 # guessed
# TODO: verify this # TODO: verify this
n_ff = int(2 * (4 * n_embd) / 3) n_ff = int(2 * (4 * n_embd) / 3)
@ -151,7 +151,7 @@ class Params:
return Params( return Params(
n_vocab = n_vocab, n_vocab = n_vocab,
n_embd = n_embd, n_embd = n_embd,
n_mult = 256, n_mult = n_mult,
n_layer = n_layer, n_layer = n_layer,
n_ctx = -1, n_ctx = -1,
n_ff = n_ff, n_ff = n_ff,
@ -174,10 +174,10 @@ class Params:
n_mult = find_n_mult(n_ff, n_embd); n_mult = find_n_mult(n_ff, n_embd);
if "max_sequence_length" in hparams: if "max_sequence_length" in config:
n_ctx = hparams["max_sequence_length"] n_ctx = config["max_sequence_length"]
elif "max_position_embeddings" in hparams: elif "max_position_embeddings" in config:
n_ctx = hparams["max_position_embeddings"] n_ctx = config["max_position_embeddings"]
else: else:
raise Exception("failed to guess 'n_ctx'. This model is unknown or unsupported.\n" raise Exception("failed to guess 'n_ctx'. This model is unknown or unsupported.\n"
"Suggestion: provide 'config.json' of the model in the same directory containing model files.") "Suggestion: provide 'config.json' of the model in the same directory containing model files.")
@ -541,7 +541,7 @@ def convert_transformers_to_orig(model: LazyModel, params: Params) -> LazyModel:
for i in itertools.count(): for i in itertools.count():
if f"model.layers.{i}.self_attn.q_proj.weight" in model: if f"model.layers.{i}.self_attn.q_proj.weight" in model:
out[f"layers.{i}.attention.wq.weight"] = permute_lazy(model[f"model.layers.{i}.self_attn.q_proj.weight"], params.n_head) out[f"layers.{i}.attention.wq.weight"] = permute_lazy(model[f"model.layers.{i}.self_attn.q_proj.weight"], params.n_head, params.n_head_kv)
out[f"layers.{i}.attention.wk.weight"] = permute_lazy(model[f"model.layers.{i}.self_attn.k_proj.weight"], params.n_head, params.n_head_kv) out[f"layers.{i}.attention.wk.weight"] = permute_lazy(model[f"model.layers.{i}.self_attn.k_proj.weight"], params.n_head, params.n_head_kv)
out[f"layers.{i}.attention.wv.weight"] = model[f"model.layers.{i}.self_attn.v_proj.weight"] out[f"layers.{i}.attention.wv.weight"] = model[f"model.layers.{i}.self_attn.v_proj.weight"]
elif f"model.layers.{i}.self_attn.W_pack.weight" in model: elif f"model.layers.{i}.self_attn.W_pack.weight" in model:
@ -1011,7 +1011,7 @@ def main(args_in: Optional[List[str]] = None) -> None:
vocab = load_vocab(vocab_dir, args.vocabtype) vocab = load_vocab(vocab_dir, args.vocabtype)
model = model_plus.model model = model_plus.model
model = do_necessary_conversions(model, params) model = do_necessary_conversions(model, params) # TODO: utilize gguf.get_tensor_name_map
output_type = pick_output_type(model, args.outtype) output_type = pick_output_type(model, args.outtype)
model = convert_to_output_type(model, output_type) model = convert_to_output_type(model, output_type)
outfile = args.outfile or default_outfile(model_plus.paths, output_type) outfile = args.outfile or default_outfile(model_plus.paths, output_type)