Problems when trying to use Llama-2 models for function calling #10
Description
When I run the following command:
generator = Generator.hf(functions, "meta-llama/Llama-2-7b-chat-hf")
I get the following error:
AttributeError Traceback (most recent call last)
Cell In[11], line 1
----> 1 function_call = generator.generate("What is the weather like today in Delaware?")
2 print(function_call)
File /local_llm_function_calling/generator.py:189, in Generator.generate(self, prompt, function_call, max_length, max_new_tokens, suffix)
174 """Generate the function call
175
176 Args:
(...)
186 FunctionCall: The generated function call
187 """
188 function_name = self.choose_function(prompt, function_call, suffix)
--> 189 arguments = self.generate_arguments(
190 prompt, function_name, max_new_tokens, max_length
191 )
192 return {"name": function_name, "parameters": arguments}
File /local_llm_function_calling/generator.py:157, in Generator.generate_arguments(self, prompt, function_call, max_length, max_new_tokens)
147 prefix = self.prompter.prompt(prompt, self.functions, function_call)
148 constraint = JsonSchemaConstraint(
149 [
150 function
(...)
155 ] # type: ignore
156 )
--> 157 generated = self.constrainer.generate(
158 prefix,
159 constraint,
160 max_length,
161 max_new_tokens,
162 )
163 validated = constraint.validate(generated)
164 return generated[: validated.end_index] if validated.end_index else generated
File /local_llm_function_calling/constrainer.py:221, in Constrainer.generate(self, prefix, constraint, max_len, max_new_tokens)
219 generation = self.model.start_generation(prefix)
220 for _ in range(max_new_tokens) if max_new_tokens else count():
--> 221 if self.advance_generation(generation, constraint, max_len):
222 break
223 return generation.get_generated()
File /local_llm_function_calling/constrainer.py:191, in Constrainer.advance_generation(self, generation, constraint, max_len)
173 def advance_generation(
174 self,
175 generation: Generation,
176 constraint: Callable[[str], tuple[bool, bool]],
177 max_len: int | None = None,
178 ) -> bool:
179 """Advance the generation by one token
180
181 Args:
(...)
189 bool: Whether the generation is complete
190 """
--> 191 done, length = self.gen_next_token(generation, constraint)
192 if done:
193 return True
File /local_llm_function_calling/constrainer.py:163, in Constrainer.gen_next_token(self, generation, constraint)
161 except SequenceTooLongError:
162 return (True, 0)
--> 163 for token in sorted_tokens:
164 generated = generation.get_generated(token)
165 fit = constraint(generated)
File /local_llm_function_calling/model/huggingface.py:63, in HuggingfaceGeneration.get_sorted_tokens(self)
54 def get_sorted_tokens(self) -> Iterator[int]:
55 """Get the tokens sorted by probability
56
57 Raises:
(...)
61 The next of the most likely tokens
62 """
---> 63 if self.inputs.shape[1] >= self.model.config.n_positions:
64 raise SequenceTooLongError()
65 gen_tokens = self.model.generate(
66 input_ids=self.inputs,
67 output_scores=True,
(...)
70 pad_token_id=self.tokenizer.eos_token_id,
71 )
File /function_calling_env/lib/python3.11/site-packages/transformers/configuration_utils.py:262, in PretrainedConfig.getattribute(self, key)
260 if key != "attribute_map" and key in super().getattribute("attribute_map"):
261 key = super().getattribute("attribute_map")[key]
--> 262 return super().getattribute(key)
AttributeError: 'LlamaConfig' object has no attribute 'n_positions'
Has anyone been able to successfully run this with Llama-2 models? If so did you run into this problem and how did you fix it?