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thesven/Falcon-11B-GPTQ-2bit
Falcon-11B-GPTQ-2bit is a text generation model from thesven. Use it when you need the model to write or continue text. It is set up for transformers.
This model is a quantized version of Falcon2-11B by tiiuae. Quantization was performed with Auto-GPTQ to 2bit.
Downloads · 30 days
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From the Hugging Face model README
This model is a quantized version of Falcon2-11B by tiiuae. Quantization was performed with Auto-GPTQ to 2bit.
from transformers import AutoTokenizer, AutoModelForCausalLM, GPTQConfig
pretrained_model_name = "thesven/falcon-11B-GPTQ-2bit"
device = "cuda:0"
# Load the tokenizer
tokenizer = AutoTokenizer.from_pretrained(pretrained_model_name)
# Load the model with the specified configuration and move to device
model = AutoModelForCausalLM.from_pretrained(
pretrained_model_name,
device_map="auto",
)
# Set EOS token ID
model.eos_token_id = tokenizer.eos_token_id
# Move model to the specified device
model.to(device)
# Define the input text
input_text = "Why is the sky blue?"
# Encode the input text
input_ids = tokenizer.encode(input_text, return_tensors="pt").to(device)
# Generate output
output = model.generate(input_ids, max_length=1000)
# Decode the generated output
decoded_output = tokenizer.batch_decode(output, skip_special_tokens=True)
# Print the decoded output
for i, sequence in enumerate(decoded_output):
print(f"Generated Sequence {i+1}: {sequence}")
Falcon2-11B is licenced under [TII Falcon License 2.0(https://falconllm-staging.tii.ae/falcon-2-terms-and-conditions.html), the permissive Apache 2.0-based software license which includes an acceptable use policy that promotes the responsible use of AI.
Research on large language models; as a foundation for further specialization and finetuning for specific usecases (e.g., summarization, text generation, chatbot, etc.)
Production use without adequate assessment of risks and mitigation; any use cases which may be considered irresponsible or harmful.
Falcon2-11B is trained mostly on English, but also German, Spanish, French, Italian, Portuguese, Polish, Dutch, Romanian, Czech, Swedish. It will not generalize appropriately to other languages. Furthermore, as it is trained on a large-scale corpora representative of the web, it will carry the stereotypes and biases commonly encountered online.
We recommend users of Falcon2-11B to consider finetuning it for the specific set of tasks of interest, and for guardrails and appropriate precautions to be taken for any production use.