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Runtime error
Runtime error
:wrench: drop reflection. add Nemotron. make default model.
Browse files- README.md +1 -1
- app.py +6 -3
- readme-generator/generate.sh +1 -1
README.md
CHANGED
@@ -1977,7 +1977,7 @@ models:
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- 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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-
-
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---
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# Overview
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- 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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---
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# Overview
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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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-
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-
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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:
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@@ -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
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@@ -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 ==
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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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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
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readme-generator/generate.sh
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@@ -20,7 +20,7 @@ $(cat ../model-cache.json \
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console.log(yamlStr);"
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)
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- Qwen/Qwen2.5-72B
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-
-
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---
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$(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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---
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$(cat body.md)
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