README.md

metadata

license: apache-2.0
model-index:
  - name: freecs/ThetaWave-7B-v0.1
    results:
      - task:
          type: text-generation
        metrics:
          - name: average
            type: average
            value: 69.17
        source:
          name: Open LLM Leaderboard
          url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard

ThetaWave-7B v0.1

This is the first model of the ThetaWave series, based on Mistral-7B.

Utilize this model as a starting point, as it necessitates further fine-tuning and reinforcement learning.

Give it a try:

from transformers import AutoModelForCausalLM, AutoTokenizer

device = "cuda"  # the device to load the model onto

model = AutoModelForCausalLM.from_pretrained("freecs/ThetaWave-7B-v0.1")
tokenizer = AutoTokenizer.from_pretrained("freecs/ThetaWave-7B-v0.1")

messages = [
    {"role": "user", "content": "Who are you?"},
]

encodeds = tokenizer.apply_chat_template(messages, return_tensors="pt")

model_inputs = encodeds.to(device)
model.to(device)

generated_ids = model.generate(model_inputs, max_new_tokens=1000, do_sample=True)
decoded = tokenizer.batch_decode(generated_ids)
print(decoded[0])

" My goal as the founder of FreeCS.org is to establish an Open-Source AI Research Lab driven by its Community. Currently, I am the sole contributor at FreeCS.org. If you share our vision, we welcome you to join our community and contribute to our mission at freecs.org/#community. "
|- GR

If you'd like to support this project, kindly consider making a donation.