Update README.md
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README.md
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@@ -56,7 +56,7 @@ This model can be deployed efficiently using the [vLLM](https://docs.vllm.ai/en/
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from vllm import LLM, SamplingParams
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from transformers import AutoTokenizer
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model_id = "
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number_gpus = 1
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sampling_params = SamplingParams(temperature=0.7, top_p=0.8, max_tokens=256)
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@@ -136,7 +136,7 @@ HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="
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--tasks mmlu_llama \
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--fewshot_as_multiturn \
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--apply_chat_template \
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@@ -148,7 +148,7 @@ HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="
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--tasks mmlu_cot_llama \
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--apply_chat_template \
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--num_fewshot 0 \
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@@ -159,7 +159,7 @@ HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="
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--tasks arc_challenge_llama \
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--apply_chat_template \
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--num_fewshot 0 \
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@@ -170,7 +170,7 @@ HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="
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--tasks gsm8k_llama \
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--fewshot_as_multiturn \
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--apply_chat_template \
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@@ -182,7 +182,7 @@ HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="
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--tasks hellaswag \
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--num_fewshot 10 \
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--batch_size auto
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@@ -192,7 +192,7 @@ HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="
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--tasks winogrande \
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--num_fewshot 5 \
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--batch_size auto
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@@ -202,7 +202,7 @@ HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="
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--tasks truthfulqa \
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--num_fewshot 0 \
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--batch_size auto
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@@ -212,7 +212,7 @@ HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="
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--apply_chat_template \
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--fewshot_as_multiturn \
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--tasks leaderboard \
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@@ -223,7 +223,7 @@ HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of
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```
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lm_eval \
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--model vllm \
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-
--model_args pretrained="
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--tasks mmlu_pt_llama \
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--fewshot_as_multiturn \
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--apply_chat_template \
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@@ -235,7 +235,7 @@ HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of
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```
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lm_eval \
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--model vllm \
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-
--model_args pretrained="
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--tasks mmlu_es_llama \
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--fewshot_as_multiturn \
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--apply_chat_template \
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@@ -247,7 +247,7 @@ HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of
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```
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lm_eval \
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--model vllm \
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-
--model_args pretrained="
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--tasks mmlu_it_llama \
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--fewshot_as_multiturn \
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--apply_chat_template \
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@@ -259,7 +259,7 @@ HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of
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```
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lm_eval \
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--model vllm \
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-
--model_args pretrained="
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--tasks mmlu_de_llama \
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--fewshot_as_multiturn \
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--apply_chat_template \
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@@ -271,7 +271,7 @@ HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of
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```
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lm_eval \
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--model vllm \
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-
--model_args pretrained="
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--tasks mmlu_fr_llama \
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--fewshot_as_multiturn \
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--apply_chat_template \
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@@ -283,7 +283,7 @@ HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of
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```
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lm_eval \
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--model vllm \
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-
--model_args pretrained="
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--tasks mmlu_hi_llama \
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--fewshot_as_multiturn \
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--apply_chat_template \
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@@ -295,7 +295,7 @@ HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of
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```
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lm_eval \
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--model vllm \
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-
--model_args pretrained="
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--tasks mmlu_th_llama \
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--fewshot_as_multiturn \
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--apply_chat_template \
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@@ -307,7 +307,7 @@ HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of
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*Generation*
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```
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python3 codegen/generate.py \
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--model
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--bs 16 \
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--temperature 0.2 \
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--n_samples 50 \
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@@ -318,14 +318,14 @@ HumanEval and HumanEval+ evaluations were conducted using Neural Magic's fork of
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*Sanitization*
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```
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python3 evalplus/sanitize.py \
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humaneval/
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```
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*Evaluation*
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```
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evalplus.evaluate \
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--dataset humaneval \
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--samples humaneval/
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```
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</details>
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from vllm import LLM, SamplingParams
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from transformers import AutoTokenizer
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model_id = "RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic"
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number_gpus = 1
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sampling_params = SamplingParams(temperature=0.7, top_p=0.8, max_tokens=256)
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic",dtype=auto,max_model_len=3850,max_gen_toks=10,tensor_parallel_size=1 \
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--tasks mmlu_llama \
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--fewshot_as_multiturn \
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--apply_chat_template \
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic",dtype=auto,max_model_len=4064,max_gen_toks=1024,tensor_parallel_size=1 \
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--tasks mmlu_cot_llama \
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--apply_chat_template \
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--num_fewshot 0 \
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic",dtype=auto,max_model_len=3940,max_gen_toks=100,tensor_parallel_size=1 \
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--tasks arc_challenge_llama \
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--apply_chat_template \
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--num_fewshot 0 \
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic",dtype=auto,max_model_len=4096,max_gen_toks=1024,tensor_parallel_size=1 \
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--tasks gsm8k_llama \
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--fewshot_as_multiturn \
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--apply_chat_template \
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic",dtype=auto,add_bos_token=True,max_model_len=4096,tensor_parallel_size=1 \
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--tasks hellaswag \
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--num_fewshot 10 \
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--batch_size auto
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic",dtype=auto,add_bos_token=True,max_model_len=4096,tensor_parallel_size=1 \
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--tasks winogrande \
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--num_fewshot 5 \
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--batch_size auto
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic",dtype=auto,add_bos_token=True,max_model_len=4096,tensor_parallel_size=1 \
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--tasks truthfulqa \
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--num_fewshot 0 \
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--batch_size auto
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic",dtype=auto,max_model_len=4096,tensor_parallel_size=1,enable_chunked_prefill=True \
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--apply_chat_template \
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--fewshot_as_multiturn \
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--tasks leaderboard \
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic",dtype=auto,max_model_len=3850,max_gen_toks=10,tensor_parallel_size=1 \
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--tasks mmlu_pt_llama \
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--fewshot_as_multiturn \
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--apply_chat_template \
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic",dtype=auto,max_model_len=3850,max_gen_toks=10,tensor_parallel_size=1 \
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--tasks mmlu_es_llama \
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--fewshot_as_multiturn \
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--apply_chat_template \
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic",dtype=auto,max_model_len=3850,max_gen_toks=10,tensor_parallel_size=1 \
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--tasks mmlu_it_llama \
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--fewshot_as_multiturn \
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--apply_chat_template \
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic",dtype=auto,max_model_len=3850,max_gen_toks=10,tensor_parallel_size=1 \
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--tasks mmlu_de_llama \
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--fewshot_as_multiturn \
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--apply_chat_template \
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```
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lm_eval \
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--model vllm \
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+
--model_args pretrained="RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic",dtype=auto,max_model_len=3850,max_gen_toks=10,tensor_parallel_size=1 \
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--tasks mmlu_fr_llama \
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--fewshot_as_multiturn \
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--apply_chat_template \
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic",dtype=auto,max_model_len=3850,max_gen_toks=10,tensor_parallel_size=1 \
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--tasks mmlu_hi_llama \
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--fewshot_as_multiturn \
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--apply_chat_template \
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```
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lm_eval \
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--model vllm \
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--model_args pretrained="RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic",dtype=auto,max_model_len=3850,max_gen_toks=10,tensor_parallel_size=1 \
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--tasks mmlu_th_llama \
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--fewshot_as_multiturn \
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--apply_chat_template \
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*Generation*
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```
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python3 codegen/generate.py \
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--model RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic \
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--bs 16 \
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--temperature 0.2 \
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--n_samples 50 \
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*Sanitization*
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```
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python3 evalplus/sanitize.py \
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humaneval/RedHatAI--Llama-3.3-70B-Instruct-FP8-dynamic_vllm_temp_0.2
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```
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*Evaluation*
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```
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evalplus.evaluate \
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--dataset humaneval \
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--samples humaneval/RedHatAI--Llama-3.3-70B-Instruct-FP8-dynamic_vllm_temp_0.2-sanitized
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```
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</details>
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