base_model, base_model_relation, library_name, pipeline_tag, license, tags
| base_model | base_model_relation | library_name | pipeline_tag | license | tags | ||||
|---|---|---|---|---|---|---|---|---|---|
| Qwen/Qwen2.5-7B-Instruct | finetune | transformers | text-generation | apache-2.0 |
|
EVOKE-ALFWorld-7B
EVOKE is a post-training method that elicits world knowledge for goal-directed decisions. This is the full model for ALFWorld, based on Qwen2.5-7B-Instruct.
Paper · Code and evaluation · Project page
Load
from transformers import AutoModelForCausalLM, AutoTokenizer
model_id = "Gnonymous/EVOKE-ALFWorld-7B"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(
model_id, torch_dtype="auto", device_map="auto"
)
ALFWorld evaluation
Follow the installation and data instructions in the GitHub repository, then run:
.venv/inference/bin/python evaluate_alfworld.py \
--model Gnonymous/EVOKE-ALFWorld-7B \
--data-root /path/to/alfworld/json_2.1.1 \
--output /path/to/results/evoke-7b \
--gpus 0
Built with Qwen. See the included LICENSE and NOTICE files.