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Model Description
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- Model type: [More Information Needed]
- Language(s) (NLP): [More Information Needed]
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- Finetuned from model [optional]: [More Information Needed]
Infrence Function
def generate(title):
# Define the roles and markers
# Define the roles and markers
prompt = prompt = f"[INST]Identify the brand from the given product title.[/INST]\n\n<TITL> {title} </TITL>\n\n"custom prompt here
print("Prompt:")
print(prompt)
encoding = tokenizer(prompt, return_tensors="pt").to("cuda:0")
output = model.generate(input_ids=encoding.input_ids,
attention_mask=encoding.attention_mask,
max_new_tokens=200,
do_sample=True,
temperature=0.01,
eos_token_id=tokenizer.eos_token_id,
top_k=0)
print()
# Subtract the length of input_ids from output to get only the model's response
output_text = tokenizer.decode(output[0, len(encoding.input_ids[0]):], skip_special_tokens=False)
output_text = re.sub('\n+', '\n', output_text) # remove excessive newline characters
print("Generated Assistant Response:")
print(output_text)
return output_text
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Model tree for 1DS/adapter-title-brand-mapping-Llama-2-7b-chat-hf-v1
Base model
meta-llama/Llama-2-7b-chat-hf