wxgeorge commited on
Commit
f02037a
1 Parent(s): 75d7eaa

:wrench: drop reflection. add Nemotron. make default model.

Browse files
Files changed (3) hide show
  1. README.md +1 -1
  2. app.py +6 -3
  3. readme-generator/generate.sh +1 -1
README.md CHANGED
@@ -1977,7 +1977,7 @@ models:
1977
  - ziniuli/Mistral-7B-ReMax-v0.1
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  - zmzmxz/NeuralPipe-7B-slerp
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  - Qwen/Qwen2.5-72B
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- - mattshumer/Reflection-Llama-3.1-70B
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  ---
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  # Overview
 
1977
  - ziniuli/Mistral-7B-ReMax-v0.1
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  - zmzmxz/NeuralPipe-7B-slerp
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  - Qwen/Qwen2.5-72B
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+ - nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
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  ---
1982
 
1983
  # Overview
app.py CHANGED
@@ -40,12 +40,14 @@ model_class_filter = {
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  # we run a few other models here as well
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  REFLECTION="mattshumer/Reflection-Llama-3.1-70B"
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  QWEN25_72B="Qwen/Qwen2.5-72B"
 
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  bigger_whitelisted_models = [
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- REFLECTION,
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- QWEN25_72B
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  ]
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  # REFLECTION is in backup hosting
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  model_class_from_model_id[REFLECTION] = 'llama31-70b-16k'
 
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  def build_model_choices():
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  all_choices = []
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  for model_class in model_cache:
@@ -72,6 +74,7 @@ def model_in_list(model):
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  key=os.environ.get('RANDOM_SEED', 'kcOtfNHA+e')
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  o = random.Random(f"{key}-{datetime.date.today().strftime('%Y-%m-%d')}")
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  initial_model = o.choice(model_choices)[1]
 
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  # this doesn't work in HF spaces because we're iframed :(
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  # def initial_model(referer=None):
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  # return REFLECTION
@@ -105,7 +108,7 @@ def respond(message, history, model):
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  history_openai_format.append({"role": "assistant", "content":assistant})
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  history_openai_format.append({"role": "user", "content": message})
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- if model == "mattshumer/Reflection-Llama-3.1-70B":
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  history_openai_format = [
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  {"role": "system", "content": REFLECTION_SYSTEM_PROMPT},
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  *history_openai_format
 
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  # we run a few other models here as well
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  REFLECTION="mattshumer/Reflection-Llama-3.1-70B"
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  QWEN25_72B="Qwen/Qwen2.5-72B"
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+ NEMOTRON="nvidia/Llama-3.1-Nemotron-70B-Instruct-HF"
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  bigger_whitelisted_models = [
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+ QWEN25_72B,
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+ NEMOTRON
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  ]
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  # REFLECTION is in backup hosting
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  model_class_from_model_id[REFLECTION] = 'llama31-70b-16k'
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+ model_class_from_model_id[NEMOTRON] = 'llama31-70b-16k'
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  def build_model_choices():
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  all_choices = []
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  for model_class in model_cache:
 
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  key=os.environ.get('RANDOM_SEED', 'kcOtfNHA+e')
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  o = random.Random(f"{key}-{datetime.date.today().strftime('%Y-%m-%d')}")
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  initial_model = o.choice(model_choices)[1]
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+ initial_model = NEMOTRON
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  # this doesn't work in HF spaces because we're iframed :(
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  # def initial_model(referer=None):
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  # return REFLECTION
 
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  history_openai_format.append({"role": "assistant", "content":assistant})
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  history_openai_format.append({"role": "user", "content": message})
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111
+ if model == REFLECTION:
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  history_openai_format = [
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  {"role": "system", "content": REFLECTION_SYSTEM_PROMPT},
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  *history_openai_format
readme-generator/generate.sh CHANGED
@@ -20,7 +20,7 @@ $(cat ../model-cache.json \
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  console.log(yamlStr);"
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  )
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  - Qwen/Qwen2.5-72B
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- - mattshumer/Reflection-Llama-3.1-70B
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  ---
25
 
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  $(cat body.md)
 
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  console.log(yamlStr);"
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  )
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  - Qwen/Qwen2.5-72B
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+ - nvidia/Llama-3.1-Nemotron-70B-Instruct-HF
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  ---
25
 
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  $(cat body.md)