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convert.py : export rope freq_base when converting CodeLlama from an HF model (#2773)
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34
convert.py
34
convert.py
@ -160,13 +160,14 @@ class Params:
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def loadHFTransformerJson(model: 'LazyModel', config_path: 'Path') -> 'Params':
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config = json.load(open(config_path))
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n_vocab = config["vocab_size"]
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n_embd = config["hidden_size"]
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n_layer = config["num_hidden_layers"]
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n_ff = config["intermediate_size"]
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n_head = config["num_attention_heads"]
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n_head_kv = config["num_key_value_heads"] if "num_key_value_heads" in config else n_head
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f_norm_eps = config["rms_norm_eps"]
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n_vocab = config["vocab_size"]
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n_embd = config["hidden_size"]
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n_layer = config["num_hidden_layers"]
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n_ff = config["intermediate_size"]
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n_head = config["num_attention_heads"]
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n_head_kv = config["num_key_value_heads"] if "num_key_value_heads" in config else n_head
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f_norm_eps = config["rms_norm_eps"]
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f_rope_freq_base = config["rope_theta"] if "rope_theta" in config else None
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n_mult = Params.find_n_mult(n_ff, n_embd)
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@ -179,15 +180,16 @@ class Params:
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"Suggestion: provide 'config.json' of the model in the same directory containing model files.")
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return Params(
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n_vocab = n_vocab,
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n_embd = n_embd,
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n_mult = n_mult,
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n_layer = n_layer,
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n_ctx = n_ctx,
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n_ff = n_ff,
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n_head = n_head,
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n_head_kv = n_head_kv,
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f_norm_eps = f_norm_eps,
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n_vocab = n_vocab,
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n_embd = n_embd,
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n_mult = n_mult,
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n_layer = n_layer,
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n_ctx = n_ctx,
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n_ff = n_ff,
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n_head = n_head,
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n_head_kv = n_head_kv,
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f_norm_eps = f_norm_eps,
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f_rope_freq_base = f_rope_freq_base,
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)
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# LLaMA v2 70B params.json
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