b-gendron commited on
Commit
f6e9257
1 Parent(s): 85c27af

Better formatting of hyperparams and code snippet

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  1. README.md +5 -4
README.md CHANGED
@@ -11,6 +11,7 @@ License: mit
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  ---
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  hyperparams used to train this model:
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  lr = 5e-4,
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  lr_schedule = constant,
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  wd=0.1,
@@ -18,17 +19,16 @@ adam_beta1=0.9, adam_beta2 = 0.95,
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  context_length=512,
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  batch_size=80,
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  gradient_accumulation_steps=16
 
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  ------ EXAMPLE USAGE ---
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  from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
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  model = AutoModelForCausalLM.from_pretrained('roneneldan/TinyStories-33M')
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-
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  tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neo-125M")
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-
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  prompt = "Once upon a time there was"
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-
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  input_ids = tokenizer.encode(prompt, return_tensors="pt")
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  # Generate completion
@@ -38,4 +38,5 @@ output = model.generate(input_ids, max_length = 1000, num_beams=1)
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  output_text = tokenizer.decode(output[0], skip_special_tokens=True)
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  # Print the generated text
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- print(output_text)
 
 
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  ---
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  hyperparams used to train this model:
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+ ```
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  lr = 5e-4,
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  lr_schedule = constant,
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  wd=0.1,
 
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  context_length=512,
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  batch_size=80,
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  gradient_accumulation_steps=16
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+ ```
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  ------ EXAMPLE USAGE ---
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+ ```py
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  from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig
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  model = AutoModelForCausalLM.from_pretrained('roneneldan/TinyStories-33M')
 
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  tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neo-125M")
 
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  prompt = "Once upon a time there was"
 
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  input_ids = tokenizer.encode(prompt, return_tensors="pt")
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  # Generate completion
 
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  output_text = tokenizer.decode(output[0], skip_special_tokens=True)
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  # Print the generated text
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+ print(output_text)
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+ ```