Edit model card

Direct Use

import transformers as tfm 

model = tfm.AutoModelForCausalLM.from_pretrained("Owaner/fineweb-falcon")
tokenizer = tfm.PreTrainedTokenizerFast.from_pretrained("Owaner/falcon_tokenizer")

example = "When habitually indulge in "
tokenized_input = tokenizer(example, return_tensors="pt", return_token_type_ids=False)
output = model.generate(
    inputs=tokenized_input["input_ids"],
    attention_mask=tokenized_input["attention_mask"],
    do_sample = True,
    max_length=100,
    temperature=0.7,
    top_k=50,
    top_p=0.95,
    num_return_sequences=5
)
output_text = tokenizer.batch_decode(output, skip_special_tokens=True)

for i, o in enumerate(output_text):
    print(f"Output {i+1}: {o}") 
  • Hardware Type: Single Nvidia A80 memory 80
  • Hours used: 2 hours
  • Cloud Provider: DataCrunch
  • Compute Region: [More Information Needed]
  • Carbon Emitted: [More Information Needed]
Downloads last month
9
Safetensors
Model size
39.6M params
Tensor type
F32
·
Inference API
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.