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from huggingface_hub import InferenceClient
import time
client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
# client = InferenceClient("meta-llama/Llama-2-70b-chat-hf")
def split_list(lst, chunk_size):
return [lst[i:i + chunk_size] for i in range(0, len(lst), chunk_size)]
def format_prompt(message, history, system_prompt):
prompt = f"<s>[INST] <<SYS>>{system_prompt}<</SYS>> [/INST] </s>" if system_prompt else "<s>"
for user_prompt in history:
prompt += f"[INST] {user_prompt} [/INST]"
prompt += f"[INST] {message} [/INST]"
return prompt
def generate(
prompt, system_prompt, history, shouldoverridehistory, historyoverride, max_new_tokens=1024, temperature=1.2, top_p=0.95, repetition_penalty=1.0,
):
temperature = float(temperature)
if temperature < 1e-2:
temperature = 1e-2
top_p = float(top_p)
generate_kwargs = dict(
temperature=temperature,
max_new_tokens=max_new_tokens,
top_p=top_p,
repetition_penalty=repetition_penalty,
do_sample=True,
seed=round(time.time()),
)
if shouldoverridehistory:
history = split_list(historyoverride[0], 2)
formatted_prompt = format_prompt(prompt, history, system_prompt)
print(formatted_prompt)
stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=False, details=True, return_full_text=False)
return stream |